Search

Introduction/purpose: The paper presents the multi-criteria Fuzzy DIBR-Fuzzy DIBR II-EWAA-BM-DEXi-Fuzzy LMAW model for choosing a location for crossing water obstacles by fording in a defense operation. After the identification of the criteria by experts in this field, the mentioned model was applied and the optimal point was determined. In order to test the consistency of the results and the validity of the model, experts were consulted again, and the sensitivity analysis and the comparative analysis were performed. Methods: The Fuzzy DIBR and Fuzzy DIBR II methods were used to determine the weighting coefficients of the identified criteria, while the aggregation of the expert opinions and the obtained values was performed using the EWAA and BM operators. To select the optimal location, the Fuzzy LMAW method was applied, while the linguistic descriptors were determined using the DEXi decision support system. Results: The proposed methodology made it possible to identify all the criteria that determine the choice of a location and the choice of the optimal point for crossing a water obstacle in a defense operation. The testing of the model by experts, the analysis of the sensitivity of the output results to changes in the weights of the criteria and the comparison of the obtained results with the results of other methods indicated the fact that the model is valid and that it gives consistent results. Conclusion: It was concluded that the multi-criteria model provides the necessary help to decision makers in conditions of imprecise and unspecified information and that it is applicable in real situations. Also, the proposed model takes into consideration all the aspects that must be considered when making such a complex decision and helps less experienced officers in the decision-making process, reducing the possibility of errors, which can result in human casualties. Finally, directions for further research in the field of overcoming water obstacles and multicriteria decision making are suggested.

Introduction/purpose: The paper presents the multi-criteria Fuzzy DIBRFuzzy DIBR II-EWAA-BM-DEXi-Fuzzy LMAW model for choosing a location for crossing water obstacles by fording in a defense operation. After the identification of the criteria by experts in this field, the mentioned model was applied and the optimal point was determined. In order to test the consistency of the results and the validity of the model, experts were consulted again, and the sensitivity analysis and the comparative analysis were performed. Methods: The Fuzzy DIBR and Fuzzy DIBR II methods were used to determine the weighting coefficients of the identified criteria, while the aggregation of the expert opinions and the obtained values was performed using the EWAA and BM operators. To select the optimal location, the Fuzzy LMAW method was applied, while the linguistic descriptors were determined using the DEXi decision support system. Results: The proposed methodology made it possible to identify all the criteria that determine the choice of a location and the choice of the optimal point for crossing a water obstacle in a defense operation. The testing of the model by experts, the analysis of the sensitivity of the output results to changes in the weights of the criteria and the comparison of the obtained results with the results of other methods indicated the fact that the model is valid and that it gives consistent results. Conclusion: It was concluded that the multi-criteria model provides the necessary help to decision makers in conditions of imprecise and unspecified information and that it is applicable in real situations. Also, the proposed model takes into consideration all the aspects that must be considered when making such a complex decision and helps less experienced officers in the decision-making process, reducing the possibility of errors, which can result in human casualties. Finally, directions for further research in the field of overcoming water obstacles and multicriteria decision making are suggested. [ABSTRACT FROM AUTHOR]

Nowadays, educational information technology is widely used in higher education teaching, but various teaching resources are not reasonably utilized and effectively managed. In order to solve such problems, this paper introduces edge computing in the basic cloud computing environment to innovate and optimize the multimedia teaching mode of higher education, proposes a VR edge cloud classroom teaching mode, and proposes a collaborative transmission and resource allocation strategy based on DIBR vision synthesis technology to optimize the teaching experience. The VR Edge Cloud Classroom teaching model is designed from three aspects: teaching methods, teaching content, and teaching evaluation. Through practical teaching, students believe that the advantages of this teaching mode are mainly rich in learning resources, conducive to learning-related knowledge and that they will achieve gains in expanding their knowledge, improving their independent learning ability and cultivating their analytical and problem-solving ability. Comparing and analyzing the teaching effect of VR edge cloud classrooms with the traditional teaching effect, there is a significant difference between the two in terms of the achievement of the total objectives (P=0.015

The selection of unmanned aerial vehicles for different purposes is a frequent topic of research. This paper presents a hybrid model of an unmanned aerial vehicle (UAV) selection using the Defining Interrelationships Between Ranked criteria (DIBR), Full Consistency Method (FUCOM), Logarithm Methodology of Additive Weights (LMAW) and grey - Evaluation based on Distance from Average Solution (G-EDAS) methods. The above-mentioned model is tested and confirmed in a case study. First of all, in the paper are defined the criteria conditioning the selection, and then with the help of experts and by applying the DIBR, FUCOM and LMAW methods, the weight coefficients of the criteria are determined. The final values of the weight coefficients are obtained by aggregating the values of the criteria weights from all the three methods using the Bonferroni aggregator. Ranking and selection of the optimal UAV from twentythree defined alternatives is carried out using the G-EDAS method. Sensitivity analysis confirmed a high degree of consistency of the solutions obtained using other MCDM methods, as well as changing the criteria weight coefficients. The proposed model has proved to be stable; its application is also possible in other areas and it is a reliable tool for decision-makers during the selection process. [ABSTRACT FROM AUTHOR]

Algorithms for converting 2D to 3D are gaining importance following the hiatus brought about by the discontinuation of 3D TV production; this is due to the high availability and popularity of virtual reality systems that use stereo vision. In this paper, several depth image-based rendering (DIBR) approaches using state-of-the-art single-frame depth generation neural networks and inpaint algorithms are proposed and validated, including a novel very fast inpaint (FAST). FAST significantly exceeds the speed of currently used inpaint algorithms by reducing computational complexity, without degrading the quality of the resulting image. The role of the inpaint algorithm is to fill in missing pixels in the stereo pair estimated by DIBR. Missing estimated pixels appear at the boundaries of areas that differ significantly in their estimated distance from the observer. In addition, we propose parameterizing DIBR using a singular, easy-to-interpret adaptable parameter that can be adjusted online according to the preferences of the user who views the visualization. This single parameter governs both the camera parameters and the maximum binocular disparity. The proposed solutions are also compared with a fully automatic 2D to 3D mapping solution. The algorithm proposed in this work, which features intuitive disparity steering, the foundational deep neural network MiDaS, and the FAST inpaint algorithm, received considerable acclaim from evaluators. The mean absolute error of the proposed solution does not contain statistically significant differences from state-of-the-art approaches like Deep3D and other DIBR-based approaches using different inpaint functions. Since both the source codes and the generated videos are available for download, all experiments can be reproduced, and one can apply our algorithm to any selected video or single image to convert it. [ABSTRACT FROM AUTHOR]

In this paper, 3D point cloud and depth map fusion system for 3D environment detection is proposed. This algorithm uses the depth map generated by virtual perspective mapping technology to assist LiDAR point cloud map information matching, and distinguishes objects according to distance and color to facilitate observation. At the same time, the depth map is used to assist in the generation of two-dimensional point cloud information to repair the missing problems to achieve the effect of restoring the point cloud information. The method solves the problems of sparse point cloud information of distant objects, reflections caused by the material of cars, and light penetration caused by glass, so that the point cloud map information can be more accurate. After a series of experiments, the accuracy rate of the proposed method can reach 91.27%, the precision of matching completeness is 91.61%, the F1-measure is 92.37%, and the recall rate can reach 93.14%. Compared with most methods, our proposed method has better performance. The proposed method successfully solves the problems that LiDAR point cloud map data will be missing and sparse due to environmental factors to achieve high-precision point cloud map.

Introduction/purpose: The paper presents the DIBR-FMARCOS model of multi-criteria decision-making for defining a location for placing a bridge over an obstacle using a heavy mechanized bridge (TMM-3). After the application of the proposed model, the sensitivity analysis of the output results was performed and it was concluded that the model is stable, i.e. that the model gives consistent results and that its application is possible in real situations. Methods: The DIBR method was used to determine the weight coefficients of the criteria, while the ranking of alternatives was performed by the FuzzyMARCOS method. Results: The application of this model has led to the selection of the location for placing a bridge from the TMM-3 set, based on the defined criteria. After applying the proposed model, the sensitivity analysis of the output results was performed and the consistency of the output results of the method was proven. Conclusion: Finally, it was concluded that the proposed model can be applied in practice, because it gives stable output results. It was also concluded that the DIBR method facilitates the process of obtaining the weight coefficients of the criteria, and the FMARCOS method copes well with unclear and inaccurate input data and has good stability. This model can be further improved by more detailed operationalization of the criteria, as well as by the use of other different methods for determining the weights of the criteria and ranking.

Based on the three rotational degrees (video in three dimensions, on the X, Y and Z axes) of freedom provided by VR, the viewer is free to control the viewing point and has six degrees of freedom (6DoF). When watching a sports game, the audience is no longer limited by the position of the camera, and can freely choose the viewing angle and position just like watching in the real world, which can greatly improve the immersion of viewing. However, the major barrier that prevents 6DoF video live from being industrialized lies in the extremely high computational complexity, of which multi-view depth estimation and Depth Image Based Rendering (DIBR) is difficult to realize. And existing devices do not have hardware interfaces that support multi-views coding technology. Therefore, we need new technologies for depth estimation and virtual view synthesis, and we need to use existing hardware coding/decoding interfaces to reduce power consumption. In this paper, we provide a 6DoF live video system, which includes multi-view depth estimation technique based on unsupervised learning, virtual viewpoint real-time rendering technology and 6DoF video coding. Experimental results demonstrate that our proposed acceleration method can speed up the original depth estimation algorithm by more than 34x, and can speed up the original DIBR algorithm by more than 168x. With our 6DoF video coding method, experimental results show that the bit rate achieves an average of 70%, 64%, 33%, 60% and 66% bitrate saving for AVC, HEVC, AV1, AVS3, VVC codec standard respectively. [ABSTRACT FROM AUTHOR]

Due to the emergence of mobile 3D devices, multi-view 3D videos are expected to play increasingly important roles in providing immersively interactive experiences to users. Compared with traditional single-view videos, it is envisaged that a multi-view 3D video requires a larger storage space and bandwidth consumption. Nevertheless, efficient caching for multi-view 3D videos in a mobile proxy has not been explored in the literature. In this paper, therefore, we first observe that the storage space can be effectively reduced by leveraging Depth Image Based Rendering (DIBR) in multi-view 3D videos. We then formulate a new cache management problem, named Adaptive View Selection and Cache Operation (AVSCO), and find the optimal policy based on Markov Decision Process (MDP). Afterward, we propose an online algorithm with a guaranteed competitive ratio to support human visual continuity in AVSCO. Then, we devise an approximate MDP to accelerate the computation of MDP by aggregating similar states to reduce the state space. Simulation and prototype implementation results manifest that the proposed algorithms can significantly improve the cache hit rate and reduce the bandwidth consumption for the remote access compared with the existing cache replacement algorithms. [ABSTRACT FROM AUTHOR]

Depth image-based rendering (DIBR) is an important technique in the 2D to 3D conversion process, which renders virtual views with a texture image and the associated depth map. However, certain problems, such as disocclusion, still exist in current DIBR systems. In this study, a new learning-based framework that models conventional DIBR synthesis pipelines is proposed to solve these problems. The proposed model adopts a coarse-to-fine approach to realize virtual view prediction and disocclusion region refinement sequentially in a unified deep learning framework that includes two cascaded joint filter block-based convolutional neural networks (CNNs) and one residual learning-based generative adversarial network (GAN). An edge-guided global looping optimization strategy is adopted to progressively reconstruct the scene structures on the novel view, and a novel directional discounted reconstruction loss is proposed for better training. In this way, our framework performs well in terms of virtual view quality and is more suitable for 2D to 3D conversion applications. The experimental results demonstrate that the proposed method can generate visually satisfactory results. [ABSTRACT FROM AUTHOR]

Introduction/purpose: The paper presents the DIBR-FMARCOS model of multi-criteria decision-making for defining a location for placing a bridge over an obstacle using a heavy mechanized bridge (TMM-3). After the application of the proposed model, the sensitivity analysis of the output results was performed and it was concluded that the model is stable, i.e. that the model gives consistent results and that its application is possible in real situations. Methods: The DIBR method was used to determine the weight coefficients of the criteria, while the ranking of alternatives was performed by the Fuzzy MARCOS method. Results: The application of this model has led to the selection of the location for placing a bridge from the TMM-3 set, based on the defined criteria. After applying the proposed model, the sensitivity analysis of the output results was performed and the consistency of the output results of the method was proven. Conclusion: Finally, it was concluded that the proposed model can be applied in practice, because it gives stable output results. It was also concluded that the DIBR method facilitates the process of obtaining the weight coefficients of the criteria, and the FMARCOS method copes well with unclear and inaccurate input data and has good stability. This model can be further improved by more detailed operationalization of the criteria, as well as by the use of other different methods for determining the weights of the criteria and ranking. [ABSTRACT FROM AUTHOR]

Depth-Image-Based-Rendering (DIBR), as one important technique in 3D video system, can be used to generate virtual views. Unfortunately, the DIBR algorithms will introduce various distortions and induce an annoying viewing experience. And it has been proved that traditional 2D assessment quality metrics are not suitable for the DIBR-synthesized views. In this paper, we propose a novel approach to assess the quality of DIBR-synthesized images. The proposed method mainly considers three kinds of DIBR-related distortions: holes distortion, strip-sharped distortion and global sharpness. Holes and strip distortions as two local features are used to characterize the local quality of DIBR-synthesized image, respectively. For the global sharpness we consider the Just Notice Difference (JND) model of human eyes and use it to extract the JND-based global difference for analyzing the global quality. Finally, we combine the holes distortion evaluation, strip distortion evaluation and global quality to infer the overall perceptual quality. Extensive experiments indicate that our method achieves higher accuracy of quality prediction than most competing metrics.

With the Depth-image-based rendering (DIBR) technique, virtual views can be drawn at any position between two reference viewpoints. However, DIBR algorithm may introduce various distortions in the synthesized images, such as holes, artifact, and stretching. This paper proposes a quality evaluation method for DIBR-synthesized images by analyzing the holes and expanded regions. First, the holes regions are obtained with the watershed algorithm and used to evaluate the quality of the DIBR-synthesized images. Then, the synthesized image is compared with the reference image in the sub-channel, and the number of different pixel values is used to assess the global quality of synthesized images. Finally, the two measures are pooled to calculate the overall quality score of the DIBR synthesized image. Experimental results show that our scheme can better predict the image quality and performs better in terms of implementation time compared with other schemes.

With the increasing prevalence of free-viewpoint video applications, virtual view synthesis has attracted extensive attention. In view synthesis, a new viewpoint is generated from the input color and depth images with a depth-image-based rendering (DIBR) algorithm. Current quality evaluation models for view synthesis typically operate on the synthesized images, i.e. after the DIBR process, which is computationally expensive. So a natural question is that can we infer the quality of DIBR-based synthesized images using the input color and depth images directly without performing the intricate DIBR operation. With this motivation, this paper presents a no-reference image quality prediction model for view synthesis via COlor-Depth Image Fusion, dubbed CODIF, where the actual DIBR is not needed. First, object boundary regions are detected from the color image, and a Wavelet-based image fusion method is proposed to imitate the interaction between color and depth images during the DIBR process. Then statistical features of the interactional regions and natural regions are extracted from the fused color-depth image to portray the influences of distortions in color/depth images on the quality of synthesized views. Finally, all statistical features are utilized to learn the quality prediction model for view synthesis. Extensive experiments on public view synthesis databases demonstrate the advantages of the proposed metric in predicting the quality of view synthesis, and it even suppresses the state-of-the-art post-DIBR view synthesis quality metrics. [ABSTRACT FROM AUTHOR]

Abstract Free viewpoint video is generated on the basis of a video plus depth (V+D) virtual point rendering framework. Because of the limited bandwidth of video transmission, depth-image-based rendering (DIBR) has become a common method. Most DIBR methods not only have holes and ghost artifacts but also have problems with time continuity, leading to frequent flickers. In this paper, we make full use of time domain information in video sequences and adjacent frames to extract the static background image of the whole scene. Furthermore, we propose a weighted-fusion hole-filling method based on static background to fill holes and maintain time continuity. Experimental results show that the proposed method can improve the quality of virtual view images and strengthen spatio-temporal continuity.

This paper proposes an improved virtual view image synthesis algorithm to overcome the drawbacks of conventional virtual view synthesis technologies in dealing with holes and artifacts. First, conduct edge detection and preparation operation on obtained depth images to reduce the holes caused by the step change of pixel value; second, use the Euclidean distance between pixels and the depth information of image to roughly integrate images; finally, conduct morphological swelling treatment on the obtained virtual images to fill the rest holes and remove artifacts. According to results of simulation experiment, the improved algorithm outperforms those applied in other papers in filling holes and removing artifacts in in the course of virtual view image synthesis.

Depth image-based rendering (DIBR) is one of the main techniques in interactive 3D video systems. But a critical problem of DIBR is that how to eliminate the holes appearing in virtual view images. In this paper, an improved depth image based virtual view synthesis algorithm is proposed. In depth map pre-processing, only local areas of the depth map with sudden changes are pre-processed by the asymmetric filter. After this, we combine the forward and inverse 3D-warping to synthesize the virtual view. Firstly, it warps the left image to the virtual view and then only reversely warps the region of the holes in the virtual view to the right view to get the lost information of holes. Compared with the traditional method which have to warp the two whole images, computation cost can be reduced by 30% efficiently. Finally, we employ an improved image inpainting based on depth information to fill hole regions. We have improved the method in two portions: 1) depth information is added to the priority computation and searching the best matching patch and 2) as the filling proceeds, the confidence term of the newly inpainted pixels is updated with the mean square error (MSE) of pixels in the target matching patch and the source matching patch. Experimental results show significant objective and subjective gains of the proposed method in comparison to the reference methods.

Depth-image-based rendering (DIBR) has become an accessible rendering technology for 3D video. A variety of digital watermarking methods have been proposed to protect the copyright of DIBR 3D video works. However, the robustness and imperceptibility of the existing methods need to be improved. Therefore, we apply the DIBR rendering features to propose a watermarking method to enhance the watermarking effect. First, to improve the robustness, we combine the DIBR rendering rules to construct steady feature data as the selection criterion of watermark embedding position. We detect the scale invariable feature transformation (SIFT) feature points from centre views and match them in every two adjacent views. Each two matched feature points construct one matching vector. The gradient-probability distributions of the vectors are used as the feature data to determine the watermark embedding position. Thus, the embedding positions are robust to the affine transformation and geometric attacks, and the watermark robustness improved. Second, to improve the imperceptibility, we design a joint watermark extraction strategy based on the similarity of the rendered left and right images. The watermark data are embedded into the centre view with low embedding strength and jointly extracted from the left and right images. This strategy guarantees the extraction accuracy while reducing the impact of watermark embedding on the original centre view. Experimental data show that the proposed method has good robustness and imperceptibility. [ABSTRACT FROM AUTHOR]

The Depth-Image-Based-Rendering (DIBR) is one of the main fundamental technique to generate new views in 3D video applications, such as Multi-View Videos (MVV), Free-Viewpoint Videos (FVV) and Virtual Reality (VR). However, the quality assessment of DIBR-synthesized views is quite different from the traditional 2D images/videos. In recent years, several efforts have been made towards this topic, but there is a lack of detailed survey in the literature. In this paper, we provide a comprehensive survey on various current approaches for DIBR-synthesized views. The current accessible datasets of DIBR-synthesized views are firstly reviewed, followed by a summary analysis of the representative state-of-the-art objective metrics. Then, the performances of different objective metrics are evaluated and discussed on all available datasets. Finally, we discuss the potential challenges and suggest possible directions for future research. [ABSTRACT FROM AUTHOR]

Abstract This paper proposes a novel method for 2D-to-3D video conversion, based on boundary information to automatically generate the depth map. First, we use the Gaussian model to detect foreground objects and then separate the foreground and background. Second, we employ the superpixel algorithm to find the edge information. According to the superpixels, we will assign corresponding hierarchical depth value to initial depth map. From the result of depth value assignment, we detect the edges by Sobel edge detection with two thresholds to strengthen edge information. To identify the boundary pixels, we use a thinning algorithm to modify edge detection. Following these results, we assign the depth value of foreground to refine it. We use four kinds of scanning path for the entire image to create a more accurate depth map. After that, we have the final depth map. Finally, we utilize depth image-based rendering (DIBR) to synthesize left and right view images. After combining the depth map and the original 2D video, a vivid 3D video is produced.

To reduce geometric distortion in three dimensional (3D) synthesized images and high computation time in the depth map preprocessing, this paper proposes a region classification based asymmetric filter for depth map preprocessing. First, the depth map can be classified into three types of region: depth continuous region, sharp depth transition regions with, and without vertical lines. To maintain 3D experience and reduce computation time, the depth value in the depth continuous region is left unchanged, such as the background region. For the sharp depth transition regions, we determine the presence or lack of vertical lines. Next, an adaptive Horizontal Gaussian filter is used to reduce rubbersheet holes generated in the region which does not contain vertical lines. Additionally, an adaptive Gaussian filter based on the vertical line direction is used to reduce geometric artifacts and further reduce the computation time compared to other asymmetric Gaussian filters used in the region which has vertical lines. The proposed algorithm can improve the quality of the Depth-image-based rendering (DIBR) virtual views by using depth sensors. According to the experiment result, the computation time is reduced by 90-95% compared with the asymmetric Gaussian filter. Moreover, the vertical line comparison and the skewness comparison show that geometric distortion is reduced obviously and the 3D experience is preserved successfully. [ABSTRACT FROM AUTHOR]

Depth image-based rendering (DIBR) plays an important role in 3D video and free viewpoint video synthesis. However, artifacts might occur in the synthesized view due to viewpoint changes and stereo depth estimation errors. Holes are usually out-of-field regions and disocclusions, and filling them appropriately becomes a challenge. In this paper, a virtual view synthesis approach based on asymmetric bidirectional DIBR is proposed. A depth image preprocessing method is applied to detect and correct unreliable depth values around the foreground edges. For the primary view, all pixels are warped to the virtual view by the modified DIBR method. For the auxiliary view, only the selected regions are warped, which contain the contents that are not visible in the primary view. This approach reduces the computational cost and prevents irrelevant foreground pixels from being warped to the holes. During the merging process, a color correction approach is introduced to make the result appear more natural. In addition, a depth-guided inpainting method is proposed to handle the remaining holes in the merged image. Experimental results show that, compared with bidirectional DIBR, the proposed rendering method can reduce about 37% rendering time and achieve 97% hole reduction. In terms of visual quality and objective evaluation, our approach performs better than the previous methods. [ABSTRACT FROM AUTHOR]

Free viewpoint video is generated on the basis of a video plus depth (V+D) virtual point rendering framework. Because of the limited bandwidth of video transmission, depth-image-based rendering (DIBR) has become a common method. Most DIBR methods not only have holes and ghost artifacts but also have problems with time continuity, leading to frequent flickers. In this paper, we make full use of time domain information in video sequences and adjacent frames to extract the static background image of the whole scene. Furthermore, we propose a weighted-fusion hole-filling method based on static background to fill holes and maintain time continuity. Experimental results show that the proposed method can improve the quality of virtual view images and strengthen spatio-temporal continuity. [ABSTRACT FROM AUTHOR]

This paper presents an efficient depth estimation technique for depth image-based rendering process in the 3-D television system. It uses three depth cues, namely linear perspective, motion information, and texture characteristics, to estimate the depth of an image. In addition, suitable weights are assigned to different components of the image based on their relative perspective position of either the foreground or the background in the scene. Experimental results on publicly available datasets validate the usefulness of the proposed technique for efficient estimation of depth maps. [ABSTRACT FROM AUTHOR]

In this paper, we proposed the design and implementation of a new stereoscopic image generation system. In the conventional system, the smoothness of depth map can reduce the incidence of image holes, but cause geometric distortions of the image depth. To solve the problems, the depth map is first refined to increase the accuracy of image depth and the quality of images. Next, we derive a hardware-oriented method for 3D warping and improve hole-filling procedures to enhance the performance of image. Finally, the circuit design is presented according to the proposed stereoscopic image generation system to achieve real-time applications. The experimental results demonstrate that the proposed system can improve by 10–27% when compared to existing methods. [ABSTRACT FROM AUTHOR]

In 3D image compression, depth image based rendering (DIBR) is one of the latest techniques where the center image (say the main view, is used to synthesise the left and the right view image) and the depth image are communicated to the receiver side. It has been observed in the literature that most of the existing 3D image watermarking schemes are not resilient to the view synthesis process used in the DIBR technique. In this paper, a 3D image watermarking scheme is proposed which is invariant to the DIBR view synthesis process. In this proposed scheme, 2D-dual-tree complex wavelet transform (2D-DT-CWT) coefficients of centre view are used for watermark embedding such that shift invariance and directional property of the DT-CWT can be exploited to make the scheme robust against view synthesis process. A comprehensive set of experiments has been carried out to justify the robustness of the proposed scheme over the related existing schemes with respect to the JPEG compression and synthesis view attack. [ABSTRACT FROM AUTHOR]

Abstract The free-view image could suffer from a viewpoint change attack, although it may be not malicious. This paper focuses not only on this viewpoint change attack, but also on the other traditional and the geometric attacks. We propose a digital watermarking scheme to protect the ownership of a free-view 2D or 3D image, such that the viewer watches the image(s) by rendering an arbitrary viewpoint image (or multiple images) with the received texture image and its depth image. First, the proposed scheme generates a special map, termed the depth variation prediction map (DVPM), to find locations that are safe from viewpoint change. A 3-level Mallat-tree 2-dimensional discrete wavelet transform (2D DWT) is also used, from which the three horizontally low-pass filtered and vertically high-pass filtered subbands are used as the watermark embedding regions, in conjunction with the DVPM. Next, Multiples of the watermark data are embedded into the three subbands, and each watermark bit is embedded into a 2D DWT coefficient by a quantization index modulation (QIM) method, where the quantization step is decided by considering the energy of each subband. In extracting the watermark data, the multiple watermark data are extracted, and the most frequent value in each bit position is taken from the extracted data to form the final data. We experiment the proposed method with various test images for the various attacks, and compare our scheme with the previous methods, to show that the proposed method has excellent performance. Highlights • A digital watermarking scheme to protect the ownership of a free-view 2D or 3D image. • A special map, termed the depth variation prediction map (DVPM) to find locations that are safe from viewpoint change. • The watermark embedding regions in conjunction with the DVPM. • The watermark embedding scheme by a quantization index modulation (QIM) method. • The blind multiple watermark data extraction. [ABSTRACT FROM AUTHOR]

This paper presents the detailed analysis of n-channel Negative Capacitance Cylindrical Gate All Around Field Effect Transistor (NC-CGAAFET) of class Metal-Ferroelectric-Insulator Semiconductor (MFIS) at 2 nm technology node and its comparison with CGAAFET (Cylindrical Gate All Around Field Effect Transistor). NC-CGAAFET shows better performance in terms of I ON , Drain Induced Barrier Lowering (DIBL), Subthreshold Swing (SS), and I ON /I OFF when compared to CGAAFET. Further, NC-CGAAFET is analyzed at different values of ferroelectric layer thickness (T FE), along with different values of spacer dielectric constant (K), spacer length (L SP) and nanowire diameter (D NW) and found that SS goes below Boltzmann's limit (60 mV/dec) and further decreases with increasing T FE. Also observed that Negative-DIBL increases as T FE increases. In addition to this, the device is optimized for NDR (Negative Differential Resistance) free operation, to be applicable for both analog and digital applications, by varying T FE. The optimized NDR free NC-CGAAFET offers SS of 59.33 mV/dec, DIBL of 13.91 mV/V, and the I ON /I OFF ratio of 3.28x higher than conventional CGAAFET by operating at low power supply (V DD ∼ 0.65V). [ABSTRACT FROM AUTHOR]

Depth-image-based rendering (DIBR) has become an important technology in 3D displaying with its great advantages.As a result,more and more 3D products copyright problems turn out.Since either the center view with depth image or the synthesized virtual views could be illegally distributed,not only the center views but also the synthesized virtual views need to be protected.A watermarking method for DIBR 3D images was proposed.After applying three-level DWT to the center image,odd-even quantization was utilized to modify the coefficients of the sub-blocks of the center image,by this way the proposed method was made robust to typical signal distortions,such as JPEG compression,noise addition and median filter.As the experimental results shown,the proposed method is much more robust to the common signal distortion attacks with lower BER (bit error rate) compared with existing methods.

Depth image-based rendering (DIBR) plays an important role in 3D video and free viewpoint video synthesis. However, artifacts might occur in the synthesized view due to viewpoint changes and stereo depth estimation errors. Holes are usually out-of-field regions and disocclusions, and filling them appropriately becomes a challenge. In this paper, a virtual view synthesis approach based on asymmetric bidirectional DIBR is proposed. A depth image preprocessing method is applied to detect and correct unreliable depth values around the foreground edges. For the primary view, all pixels are warped to the virtual view by the modified DIBR method. For the auxiliary view, only the selected regions are warped, which contain the contents that are not visible in the primary view. This approach reduces the computational cost and prevents irrelevant foreground pixels from being warped to the holes. During the merging process, a color correction approach is introduced to make the result appear more natural. In addition, a depth-guided inpainting method is proposed to handle the remaining holes in the merged image. Experimental results show that, compared with bidirectional DIBR, the proposed rendering method can reduce about 37% rendering time and achieve 97% hole reduction. In terms of visual quality and objective evaluation, our approach performs better than the previous methods.

In this paper, a stereoview to multiview conversion system, which includes stereo matching and depth image-based rendering (DIBR) hardware designs, is proposed. To achieve an efficient architecture, the proposed stereo matching algorithm simply generates the raw matching costs and aggregates cost based on 1D iterative aggregation schemes. For the DIBR architecture, an inpainting-based method is used to find the most similar patch from the background, according to depth information. The simulation results show that the designed architecture achieves an averaged peak signal-to-noise ratio of 30.2 dB and structure similarity of 0.94 for the tested images. The hardware design for the proposed 2D to 3D conversion system operates at a maximum clock frequency of 160.2 MHz for outputting 1080p ($1920 \times 1080$) video at 60 frames per second. [ABSTRACT FROM AUTHOR]

Highlights • We propose a new disparity control method for visual comfort in multiview displays. • Foreground object extraction is applied for free disparity adjustment and natural texture synthesis. • An effective and efficient exemplar-based inpainting algorithm is proposed. • Translucent cracks are removed by using segmentation results. Abstract Among the rapidly growing three-dimensional technologies, multiview displays have drawn great research interests in three-dimensional television due to their adaption to the motion parallax and wider viewing angles. However, multiview displays still suffer from dazzling discomfort on the border of viewing zones. Leveraging on the separability of scene via foreground segmentation, we propose a novel virtual view synthesis method for depth-image-based rendering to alleviate the discomfort. Foreground objects of interest are extracted to segment the whole image into multiple layers, which are further warped to the virtual viewpoint in order. To alleviate the visual discomfort, global disparity adjustments and local depth control are performed for specific objects in each layer. For the post-processing, we improve an exemplar-based inpainting algorithm to tackle the disoccluded areas. Experimental results demonstrate that our method achieves effective disparity control and generates high-quality virtual view images. [ABSTRACT FROM AUTHOR]

Depth-image-based-rendering (DIBR) plays an important role in view synthesis for free-viewpoint videos. The warping process in DIBR causes geometric displacement, which distributes intensively around edges, and the subsequent rendering process results in the impairment of edges. Traditional 2D image quality metrics are limited in the quality evaluation of DIBR-synthesized images. In this paper, we present a reduced-reference quality metric for DIBR-synthesized images by only extracting several feature values, namely multi-scale Edge Intensity Similarity (EIS). The original and synthesized images are first downsampled to generate images with different resolutions. Then an edge detection process is conducted on each scale and the edge intensity is calculated. The similarity of the edge intensity between each downsampled original image and the corresponding synthesized image is computed. Finally, the average similarity is calculated as the quality score of the DIBR-synthesized image. Experiments conducted on IRCCyN/IVC DIBR image and video databases demonstrate that the proposed method overall outperforms traditional 2D and existing DIBR-targeted quality metrics. [ABSTRACT FROM AUTHOR]

Highlights • We propose a no-reference quality metric for DIBR-synthesized videos. • A two-stage flickering region detection method is proposed. • The experiments have demonstrated the best performance of the proposed method. Depth-image-based-rendering (DIBR) is the most popular view synthesis method. The rendering process in DIBR introduces artifacts to synthesized views. Temporal inconsistency of these artifacts causes flickering, which is one of the dominant distortions in DIBR-synthesized videos. We propose a no-reference quality index for DIBR-synthesized videos. A two-stage flickering region detection method is first proposed by calculating the gradient distance between the matching blocks in adjacent frames followed by a refinement operation. Subsequently, the distortion intensity of flickering regions is measured in singular value decomposition domain. The average flickering intensity is computed as the quality score. Experimental results show that our method outperforms the state-of-the-arts on the IRCCyN/IVC database and ranks the second on the SIAT database, which is only slightly worse than the best-performing one. Furthermore, the presented method is applied to improve the performances of existing metrics and benchmark DIBR algorithms, which achieves very promising results for both tasks. [ABSTRACT FROM AUTHOR]