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There are numerous criteria which are being used to measure camera performance and for determining such criteria, different tests are applied in different test environments. Within this framework, color accuracy testing at camera performance is one of foremost of such tests. In the scope of this paper, a method has been proposed to reduce user interaction in the color accuracy tests in the literature. At the same time, with the color constancy concept, it has been shown that color variation between the different test setups should also be considered as an important criterion on the camera performance.

Inpainting applications include object removal on images and videos, crack filling, error concealment, texture synthesis, where in this paper, its usage for image coherence and perspective emphasis on video frames in 2D image-to-video conversion system is analysed. Besides, the performance of different techniques in object removal and image reconstruction is compared using visual experiments and quality metrics.

A vehicle classification system, which uses features based on radiometry, is developed for single band infrared (IR) image sequences. In this context, the process is divided into three components. These are moving vehicle detection, radiance estimation, and classification. The major contribution of this paper lies in the usage of the radiance values as features, other than the raw output of IR camera output, to improve the classification performance of the detected objects. The motivation behind this is that each vehicle class has a discriminating radiance value that originates from the source temperature of the object modified by the intrinsic characteristics of the radiating surface and the environment. As a consequence, significant performance gains are achieved due to the use of radiance values in classification for the utilized measurement system.

In this paper, an application of short video synthesis from single frame images is realized and a comparative analysis of different methods on image inpainting, which is a computationally costly part of the whole procedure, is provided. Our work is fortified with experiments in order to measure the computational performances and efficiencies of the proposed method and the ones existing in literature.

In this study, we propose a method for panoramic background subtraction by using Pan-Tilt cameras in real-time. The proposed method is based on parallelization of image registration, panorama generation and background subtraction operations to run on Graphics Processing Unit (GPU). Experiments results showed that GPU usage increases speed of the algorithm 33 times without considerable performance loss and makes working real-time possible.

The Sign Language Recognition (SLR) Problem is a highly important research topic, because of its ability to increase the interaction between the people who are hearing-impaired or impediment in speech. We propose a simple but robust system. The proposed system consists of three main steps. First we apply segmentation to the face and hand region by using Fuzzy C-Means Clustering (FCM) and Thresholding. FCM is a clustering technique which employs fuzzy partitioning, in an iterative algorithm. After the face and hands are segmented, the feature vectors are extracted. The feature vectors are chosen among the low level features such as the bounding ellipse, bounding box, and center of mass coordinates, since they are known to be more robust to segmentation errors due to low resolution images. In total there are 23 features for each hand. After the feature vectors are extracted, they are used for recognition with discrete Hidden Markov Model (HMM). Recognition stage is composed of two stages, namely training and classification. The Baum Welch algorithm is used for HMM training. In classification part the likelihood of each HMM is calculated and the HMM with the highest likelihood is chosen. In order to measure the success rate of the system, the eNTERFACE dataset is used. In this dataset 8 different American Sign Language example classified and in user independent case, is shown to be working with 94.19% accuracy.

We address efficient compression and real-time streaming of stereoscopic video over the current Internet. We first propose content-adaptive stereo video coding (CA-SC), where additional coding gain, over that can be achieved by exploiting only inter-view correlations, is targeted by down-sampling one of the views spatially or temporally depending on the content, based on the well-known theory that the human visual system can perceive high frequencies in three-dimensional (3D) from the higher quality view. We also developed stereoscopic 3D video streaming server and clients by modifying available open source platforms, where each client can view the video in mono or stereo mode depending on its display capabilities. The performance of the end-to-end stereoscopic streaming system is demonstrated using subjective quality tests.

In this paper, scene recognition problem is investigated in detail by exploiting scene representation, dimension reduction and classification stages. Unlike the other studies, the proposed algorithm has preferred to model the overall structure of the scene instead of an object-based proposal. For that purpose, some of the visual representations like MPEG-7, Gist, BoW, Vlad and Fisher, are classified singly or jointly with Support Vector Machine and Random Forest. The evaluation tests are conducted on MIT indoor dataset [2] and from the results, %31 average precision has been attained by combining Scalable Color, Homogeneous Texture and Vlad with Support Vector Machine.

Technological developments and increases of the copyright infringements have led a demand on developing automatic video copy detection systems. Generally, for this task, even if visual local descriptors are preferred, descriptors should be indexed according to make an effective search. In this work, performance of three indexing methods which are defined in literature is compared for video copy detection task. Additionally estimating geometric relation between video frames has positive effect on performance is shown. Evaluation of proposed methods are tested on TRECVID 2009 content based video copy detection dataset and from obtained results, product quantization method yields much more accurate result with respect to classical bag-of-word method is observed.

In this study, 3D video streaming is taken from a different perspective: how 3D streaming will adapt if both the streamer and the receiver are mobile? The full system chain is completed on mobile devices. Video is captured from a stereo camera pair, compressed by using H.264/AVC compression standard and streamed on TCP on a low power embedded system with OMAP3530 SoC ARM processor. A mobile device with autostereoscopic display is used on the receiver side. Being based on mobile devices, this system permits the possibility of 3D video communication and 3D streaming between mobile recipients on wireless network. For the system competence, the performance is tested and the relevant results are presented.

In recent years intelligent transportation systems has been an active research area in computer vision. This work aims to classify vehicles as car, van or truck by using videos which are taken from an uncalibrated camera which sees any highway from above. In this work, moving blobs are detected by a background-foreground extraction algorithm, classification is done by extracting the blob features and histogram of oriented gradients features of detected blobs and by giving those features to support vector machine classifier. Suggested method has been tried on 2 different traffic video and results have been presented.

This paper proposes a new maximum a posteriori (MAP) based super-resolution (SR) image reconstruction method targeting edges and textures in images. Unlike conventional MAP based SR image reconstruction methods a spatially varying image prior is employed which is updated according to the frequency content of the reconstructed image at each iteration at different locations. Two alternative methods based on discrete cosine transforms (DCT) and Gabor filters are proposed for determining the image prior. The proposed method is validated through simulations and real experiments which clearly demonstrates significant visual improvements especially on edges and textures compared to state-of-the-art SR methods.

This study presents the stereo video capture and compression on embedded platforms in real time and streaming of the video to mobile devices over a wireless network, as an end-to-end system. The major components of the system are the state-of-the art compression standard H.264/AVC used with side-by-side representation of stereo video on the OMAP3530 SoC (SystemonChip) ARM processor and the mobile device with autostereoscopic display at the receiver side. With the presented architecture, 3D video communication between the mobile users connected to a wireless network is made possible. Furthermore, performance tests are conducted for the system and results are provided in this study.

In this paper, a new color super-resolution (SR) image reconstruction method for HSV domain is presented. Applying classical SR algorithms to each channel of the HSV video causes an artifact due to the cyclic nature of the hue channel. Proposed method solves this problem without converting the HSV video to RGB video. The proposed method reconstructs the saturation and value channels using maximum aposteriori based SR algorithm. For the hue channel the problematic pixels causing the artifacts are masked and a nearest neighbor interpolation is applied. The proposed method is compared to the classical approach where HSV video is converted to RGB domain and each channel is processed by a MAP based SR algorithm. Peak-signal-to-noise-ratio (PSNR) measures show that the proposed approach does not lower the PSNR values. In this paper, it has also been shown that increasing the resolution of the hue channel does not affect the detail perception. Hence applying SR methods to only S and V channels is sufficient to increase the real-time performance of the image processing systems.

Date of Conference: 26-29 September 2010 Conference Name: 17th International Conference on Image Processing, IEEE 2010 In this paper, we study the effect of limited amplitude resolution (pixel depth) in super-resolution problem. The problem we address differs from the standard super-resolution problem in that amplitude resolution is considered as important as spatial resolution. We study the trade-off between the pixel depth and spatial resolution of low resolution (LR) images in order to obtain the best visual quality in the reconstructed high resolution (HR) image. The proposed framework reveals great flexibility in terms of pixel depth and number of LR images in super-resolution problem, and demonstrates that it is possible to obtain target visual qualities with different measurement scenarios including images with different amplitude and spatial resolutions.

In this paper, we present a complete framework of an end-to-end error resilient transmission of 3D video over Digital Video Broadcasting - Handheld (DVB-H) and provide an extensive analysis of coding and transmission parameters. We perform the analysis for different coding and error resilience schemes using different contents coded at different bitrate levels. Throughout the experiments, we investigate the effects of video content type, video bitrate, coding method and unequal protection level for different channel conditions. The results show that Multi-view Coding (MVC) coding outperforms Simulcast and distribution of available bitrate between video quality and Forward Error Correction (FEC) protection is an important factor in different channel conditions.

This paper proposes two different methods in order to improve the performance of traffic sign detection process. These methods are used for efficient and robust detection of red or blue colored, circular, octagonal, rectangular and triangular traffic signs. Proposed methods use both color and shape features of the traffic signs. Both of the methods gather the color and edge information of the image in order to form a search domain for the shape based detection algorithm. The main difference between the methods appears in the fusion process of color and shape features of the gathered images. Although methods employ different algorithms for color segmentation, they both use HSV color domain. Tests on static images show improvement especially on false positive and detection rate.

In this paper a novel edge-preserving super-resolution (SR) image reconstruction method is proposed. The proposed maximum a-posteriori (MAP) based estimator uses gradient direction and amount for optimal noise reduction while preserving the edges. Compared to the other edge-preserving methods, the proposed algorithm uses the gradient direction for optimum regularization. The proposed method estimates gradient amplitude and direction at each iteration. This gradient map guides the SR reconstruction stage through iterations. Proposed method is compared against other traditional super resolution methods. Peak-signal-to-noise-ratio (PSNR) measures and illustrations clearly show that the proposed method is successful especially on edge structures in images.

We consider an error-resilient stereoscopic streaming system that uses an H.264-based multiview video codec and a rateless Raptor code for recovery from packet losses. One aim of the present work is to suggest a heuristic methodology for modeling the end-to-end rate-distortion (RD) characteristic of such a system. Another aim is to show how to make use of such a model to optimally select the parameters of the video codec and the Raptor code to minimize the overall distortion. Specifically, the proposed system models the RD curve of video encoder and performance of channel codec to jointly derive the optimal encoder bit rates and unequal error protection (UEP) rates specific to the layered stereoscopic video streaming. We define analytical RD curve modeling for each layer that includes the interdependency of these layers. A heuristic analytical model of the performance of Raptor codes is also defined. Furthermore, the distortion on the stereoscopic video quality caused by packet losses is estimated. Finally, analytical models and estimated single-packet loss distortions are used to minimize the end-to-end distortion and to obtain optimal encoder bit rates and UEP rates. The simulation results clearly demonstrate the significant quality gain against the nonoptimized schemes.

Distributed Video Coding (DVC) is a new coding paradigm, based on two information-theoretic results, which allows exploiting source statistics at the decoder only. This architecture, therefore, enables very simple encoders to be used in video coding. Wyner-Ziv video coding is a particular case of DVC which deals with lossy source coding where side information is available at the decoder only. In this paper, the performance improvement of Wyner-Ziv coding by using better side information generated by motion compensated frame interpolation algorithms proposed in literature is examined.

In this work, we propose a stereoscopic video streaming system that uses rateless codes (Raptor codes) as the error protection scheme. Initially, we model the rate-distortion (RD) curve of video encoder and performance of channel codec. Then, we estimated the distortion on the stereoscopic video quality caused by packet losses. Finally, analytical models and estimated single packet loss distortions are used to minimize the end-to-end distortion and obtain optimal encoder bit rates and unequal error protection (UEP) rates. The simulation results clearly demonstrates the significant quality gain against the non-optimized schemes.

In this paper, we propose a distributed 3D dynamic mesh coding system. The system is based on Slepian and Wolf's and Wyner and Ziv's information-theoretic results. Our system extends the ideas in distributed video coding to 3D dynamic meshes with constant connectivity. The connectivity of the sequence and key frames are encoded and decoded by a conventional static mesh coder. The Wyner-Ziv frames are encoded independent of key frames but decoded jointly with decoded key frames. The joint decoding is performed by the low density parity check codes and the side information generated by linear interpolation of decoded key frames. Experimental results show that better rate-distortion performance is obtained compared to encoding each frame by a static mesh coder.

Image fusion is an important application for increasing the information content of an image sensed by different sensors. Different detail information of the same scene sensed by different sensors are combined in a single image. In this paper, a system implementation for the fusion of LWIR and MWIR images is proposed. The proposed algorithm consists of image enhancement, registration and the fusion parts.

Date of Conference: 7-9 May 2007 Conference Name: 3DTV Conference, IEEE 2007 In this paper, error resilient stereoscopic video streaming problem is addressed. Two different Forward Error Correction (FEC) codes namely Systematic LT and RS codes are utilized to protect the stereoscopic video data against transmission errors. Initially, the stereoscopic video is categorized in 3 layers with different priorities. Then, a packetization scheme is used to increase the efficiency of error protection. A comparative analysis of RS and LT codes are provided via simulations to observe the optimum packetization and UEP strategies.

Date of Conference: 12-13 November 2007 Conference Name: Packet Video 2007 - 16th International Packet Video Workshop A near optimal streaming system for stereoscopic video is proposed. Initially, the stereoscopic video is separated into three layers and the approximate analytical model of the Rate-Distortion (RD) curve of each layer is calculated from sufficient number of rate and distortion samples. The analytical modeling includes the interdependency of the defined layers. Then, the analytical models are used to derive the optimal source encoding rates for a given channel bandwidth. The distortion in the quality of the stereoscopic video that is caused by losing a NAL unit from the defined layers is estimated to minimize the average distortion of a single NAL unit loss. The minimization is performed over protection rates allocated to each layer. Raptor codes are utilized as the error protection scheme due to their novelty and suitability in video transmission. The layers are protected unequally using Raptor codes according to the parity ratios allocated to the layers. Comparison of the defined scheme with two other protection allocation schemes is provided via simulations to observe the quality of stereoscopic video.

We propose a blind watermarking method where the watermark is a hologram itself. In the proposed approach, the quantized phase of the hologram is embedded into the wavelet-transformed host image using quantization index modulation. In the detection stage, wavelet transform of the watermarked image followed by a minimum distance decoder is used. The proposed method is blind since it requires only information about the quantizers and the parameters of the hologram recording process. The robustness of the proposed technique is tested against several attacks such as filtering, compression, occlusion, and cropping. Moreover, we discuss the effect of quantization of the hologram on the reconstruction quality.

H.264 is the current state-of-the-art monoscopic video codec providing almost twice the coding efficiency with the same quality comparing the previous codecs. With the increasing interest in 3D TV, multi-view video sequences that are provided by multiple cameras capturing the three dimensional objects and/or scene are more widely used. Compressing multi-view sequences independently with H.264 (simulcast) is not efficient since the redundancy between the closer cameras is not exploited. In order to reduce these redundancies, we propose a multi-view video codec based on H.264 using disparity estimation/compensation as well as motion estimation/compensation. In order to effectively search for disparity/motion without increasing computational complexity, we modified the buffering structure of H.264 and implemented several referencing modes. Our results show that for closely located cameras, our codec outperforms simulcast H.264 coding. For sparsely located cameras, our method can still improve coding gain depending on the video characteristics.

In this paper, we propose a blind watermarking method where watermark is chosen as the hologram of the signal to be embedded. In the proposed approach the quantized phase of the hologram is embedded into an image using quantization index modulation (QIM). The robustness of the proposed technique is tested against several attacks such as filtering, compression, occlusion and cropping. Also the effects of quantization of the hologram on the reconstruction quality are demonstrated.

Today, stereoscopic and multi-view video are among the popular research areas in the multimedia world. In this study, we have designed and built a platform consisting of stereo-view capturing, real-time transmission and display. At the display stage, end users view video in 3D by using polarized glasses. Multi-view video is compressed in an efficient way by using multi-view video coding techniques and streamed using standard real-time transport protocols. The entire system is built by modifying available open source systems whenever possible. Receiver can view the content of the video built from multiple channels as mono or stereo depending on its display and bandwidth capabilities.

This paper presents and compares two multiple description schemes for coding of stereoscopic video, which are based on H.264. The SS-MDC scheme exploits spatial scaling of one view. In case of one channel failure, SS-MDC can reconstruct the stereoscopic video with one view low-pass filtered. SS-MDC can achieve low redundancy (less than 10%) for video sequences with lower inter-view correlation. MS-MDC method is based on multi-state coding and is beneficial for video sequences with higher inter-view correlation. The encoder can switch between these two methods depending on the characteristics of video.

Textured motion – generally known as dynamic or temporal texture – analysis, classification, synthesis, segmentation and recognition is popular research areas in several fields such as computer vision, robotics, animation, multimedia databases etc. In the literature, several algorithms are proposed to characterize these textured motions such as stochastic and deterministic algorithms. However, there is no study which compares the performances of these algorithms. In this paper, we carry out a complete comparison study. Also, improvements to deterministic methods are given.

In order to compress stereo image pairs effectively, disparity compensation is the most widely used method. In this paper we examined the effects of using different disparity maps and their properties in an embedded JPEG2000 based disparity compensated stereo image coder. These properties include the block size, estimation method and the resulting entropy of the disparity map. Experimental results show that basic block matching gives better results than ground truth, especially on occluded regions and boundaries.

In this paper, a new face recognition system, GAYE, is presented. GAYE is a fully automatic system that detects and recognizes faces in cluttered scenes. The input of the system is any digitized image/image sequence that includes face/faces. The basic building blocks of the system are face detection, feature extraction and feature comparison. Face detection is based on skin color segmentation. For feature extraction, a novel approach is proposed that depends on the Gabor wavelet transform of the face image. By comparing facial feature vectors system finally makes a decision if the incoming person is recognized or not. Real time system tests show that GAYE achieves a recognition ratio over %90.

We suggest a compound full-reference stereo-video quality metric composed of two components: a monoscopic quality component and stereoscopic quality component. While the former assesses the trivial monoscopic perceived distortions caused by blur, noise, contrast change etc., the latter assesses the perceived degradation of binocular depth cues only. We use the structural similarity index as a measure for perceptual similarity and design a multiscale algorithm for obtaining a perceptual disparity map and a stereo-similarity map to be used in the suggested metric. We verify the performance of the metric with subjective tests on distorted stereo images and coded stereo-video sequences with a final aim to build a perceptually-aware feedback for a H.264 based stereo-video encoder