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This paper proposes a cost-effective VLSI architecture to improve the three-step search (TSS) algorithm for efficient motion estimation. A weighted SAD is defined as the new distortion measure instead of SAD for motion vector selection to remedy the fault of the TSS algorithm. The proposed TSS architecture is superior to conventional TSS architecture in terms of coding performance. Moreover, the additional hardware implementation cost of the proposed architecture is relatively negligible. The proposed architecture achieves best tradeoff in terms of speed and hardware cost. [ABSTRACT FROM AUTHOR]

Spatially Squeezed Surround Audio Coding (S3AC) was introduced as an approach to multi-channel audio compression which specifically aims to preserve original source localization information. In this paper, extensions to S3AC that allow for the accurate coding of independent spatial sources overlapped in both frequency and time are described; these use compact side information. An evaluation of the coder applied to tone and band-pass spatial sources shows that S3AC offers improved source localization performance while maintaining bit-rates, when compared with other state-of-the-art spatial audio coders. [ABSTRACT FROM AUTHOR]

As is well known, in video applications the former P frames are more important than the subsequent P frames in coding/decoding order due to the inter-prediction architecture adopted by the advanced video coding standards. A source marking mechanism based on this fact is proposed accordingly in this paper, along with an improved two rate three color maker (ITRTCM) scheme, which takes into account both the source mark value of a packet and the current network status. The results of ITRTCM are compared with those of the two rate three color marker (TRTCM), the enhanced token bucket three color marker (ETBTCM) and the TypeMapping method. [ABSTRACT FROM AUTHOR]

A watermarking system for embedding textile care labels directly onto fabric designs is proposed, and its stochastic properties are analyzed. Under the assumption that pixel values are independently and identically distributed with finite mean and variance, we derive i) the expected mean squared error between the original and watermarked images (transparency); and ii) an upper bound on the average absolute change to DCT coefficients of the watermarked image after one application of simulated fading (robustness). Experimental results demonstrate that the proposed scheme preserves image fidelity well and is very robust under simulated fading. [ABSTRACT FROM AUTHOR]

Blog has received lots of attention since the revolution of Web 2.0 and has attracted millions of users to publish information on it. As time goes by, information seeking in this new media becomes an emergent issue. In our paper, we take multiple features unique in blogs into account and propose a novel algorithm to rank the blog posts in blog search. Coherence between the query type and blogger interest, document relevance and freshness are combined linearly to produce the final ranking score of a post. Specifically, we introduce a user modeling method to capture interests of bloggers. In our experiments, we invite volunteers to complete several tasks and their time cost in the tasks is taken as the primary criteria to evaluate the performance. The experimental results show that our algorithm outperforms traditional ones. [ABSTRACT FROM AUTHOR]

A multi-resolution model often costs more storage space, its communications from the CPU to the graphics system is the bottleneck of the visualization process. In this paper, a multi-resolution mesh and a primitive are proposed. The primitive is used both in the storage stage and in the rendering stage, decreasing the storage size of model and the transmission amount of vertices to the graphics system. The efficiency is measured by means of tests and results compared with the previous, obtaining better storage space cost and transmission cost. [ABSTRACT FROM AUTHOR]

The Taverna workbench allows constructing highly complex analyses over life sciences data and computational resources. It provides access over 1000 of bioinformatic services, e.g., analysis algorithms for comparing genome sequences, and facilitates the construction of bioinformatic workflows. These workflows make tacit procedural bioinformatics explicit and as such lend themselves for being used in bioinformatics education. However, until now, no Taverna e-learning service exists. In this paper, we describe how Taverna can be used for learning and the services that need to be integrated in Taverna for that purpose. This includes a digital library of multimedia resources since multimedia, especially visualization, plays an important role in bioinformatics. Equally important is an intelligent educational service that automatically assembles learning activities and resources into a pedagogically coherent whole. [ABSTRACT FROM AUTHOR]

We propose a novel algorithm for the de-speckling of SAR images which exploits a priori statistical information from both the spatial and wavelet domains. In the spatial domain, we apply the Method-of-Log-Cumulants (MoLC), which is based on Mellin transform, in order to locally estimate parameters corresponding to an assumed Generalized Gaussian Rayleigh (GGR) model for the image. We then compute classical cumulants for the image and speckle models and relate them into their wavelet domain counterparts. Using wavelet cumulants, we separately derive parameters corresponding to an assumed generalized Gaussian (GG) model for the image and noise wavelet coefficients. Finally, we feed the resulting parameters into a Bayesian maximum a priori (MAP) estimator, which is applied to the wavelet coefficients of the log-transformed SAR image. Our proposed method outperforms several recently proposed de-speckling techniques both visually and in terms of different objective measures. [ABSTRACT FROM AUTHOR]

Objective image quality assessment (QA), which automatically evaluates the image quality consistently with human perception, is essentially important for numerous image and video processing applications. We propose a new objective QA method for full reference model based on the energy of structural distortion (ESD). Firstly, we collect the characteristics of the structural information by the normalization processing for the reference image. Secondly, the information of ESD is gained by projecting the image onto the characteristic signal of the structural information independently. Finally the objective quality score is obtained by computing the differences of ESD between the reference and distorted images. In this paper, we propose one implementation with simple parameters for our image QA. Experimental results show that the proposed method is well consistent with the subjective quality score. [ABSTRACT FROM AUTHOR]

In this paper, an automatic approach for detecting and extracting panels in a color comic image is proposed. Panel extraction is challenging because the background color, the background pixel locations, the panel shapes and the panel layout are not known in advance. In our approach, uniform color stripes are first identified and used as separators to segment the color comic page image into sub-regions in a recursive manner. Panels are recognized as the sub-regions that cannot be further segmented. The structure of the panels is thus obtained in the extraction process and it contains the layout of the panels as well as the reading order. Panel extraction is useful because: 1) the extracted panels can be better fitted into a handheld device for viewing; and 2) the panels can then be further analyzed to extract features used for content based indexing and retrieval. [ABSTRACT FROM AUTHOR]

There are many applications, for example image copyright protection, where transformed images of a given test image need to be identified. The solution to the identification problem consists of two main stages. In stage one, certain representative features are detected for all images. In stage two, the representative features of the test image and the stored images are compared to identify the transformed images for the test image. We have reported the technique to extract robust representative features - corners - in our previous work [1]. This paper will focus on our stage-two work on effective corner matching technique for transformed image identification. Experimental results show that the proposed corner matching technique is very much effective in identifying the transformed images for a given test image. [ABSTRACT FROM AUTHOR]

Image hash function based on the image content has applications in watermarking, authentication and image retrieval. This paper presents an algorithm for generating an image hash that is robust against content-preserving modifications and at the same time, is capable of detecting malicious tampering. Robust features are first extracted from the discrete wavelet transform followed by the Radon transform. Probabilistic quantization is then used to map the feature values to a binary sequence. Results show that the proposed method can resist perceptually insignificant modifications such as compression, filtering, scaling and rotation. It is also able to successfully detect content changing attacks such as insertion of foreign objects. [ABSTRACT FROM AUTHOR]

Automatic image annotation (AIA) refers to the association of words to whole images which is considered as a promising and effective approach to bridge the semantic gap between low-level visual features and high-level semantic concepts. In this paper, we formulate the task of image annotation as a multi-label multi class semantic image classification problem and propose a simple yet effective method: hybrid ensemble learning framework in which multi-label classifier based on uni-modal features and ensemble classifier based on bi-modal features are integrated into a joint classification model to perform multi-modal multi-label semantic image annotation. We conducted experiments on two commonly-used keyframe and image collections: MediaMill and Scene dataset including about 40,000 examples. The empirical studies demonstrated that the proposed hybrid ensemble learning method can enhance a given weak multi-label classifier to some extent, showing the effectiveness of our proposed method when limited number of multi-labeled training data is available. [ABSTRACT FROM AUTHOR]

People may make mistakes in writing a Chinese character. In this paper, we apply error-tolerant graph matching to find the stroke production errors in people's handwriting of Chinese characters. A set of edit operations to transform one graph into another are defined for achieving this purpose. The matching procedure is denoted as a search problem of finding the minimum edit distance. The A* algorithm is used to perform the searching. Experiments show that the proposed method outperforms existing algorithms in identifying stroke production errors. The proposed method can help in Chinese handwriting education by providing feedback to correct users who have stroke production errors in writing a Chinese character. [ABSTRACT FROM AUTHOR]

Sign language recognition (SLR) with large vocabulary and signer independency is valuable and is still a big challenge. Signer adaptation is an important solution to signer independent SLR. In this paper, we present a method of etyma-based signer adaptation for large vocabulary Chinese SLR. Popular adaptation techniques including Maximum Likelihood Linear Regression (MLLR) and Maximum A Posteriori (MAP) algorithms are used. Our approach can gain comparative results with that of using words, but we only require less than half data. [ABSTRACT FROM AUTHOR]

For the seamless integration of synthetic objects within video images, generating consistent illumination is critical. This paper presents an interactive rendering system using a Graphics Process Unit-based (GPU) irradiance environment map. A camcorder with a fisheye lens captures environmental information and constructs the environment map in real-time. The pre-filtering method, which approximates the irradiance of the scene using 9 parameters, renders diffuse objects within real images. This proposed interactive common illumination system based on the GPU can generate photo-realistic images at 18 ~ 20 frames per second. [ABSTRACT FROM AUTHOR]

In this paper, we propose a practical design and implementation of multi-channel High Definition (HD) and Standard Definition (SD) MPEG-2 video streaming system using server-side video rate adaptation and rate shaping over digital community network. For video rate adaptation, we employ Program Clock Reference (PCR) embedded in the MPEG-2 streams to enhance packet timing control precision and regulate the transmission rate in a refined way. For rate shaping, we introduce Traffic Control (TC) ingeniously to separate streams of different channels at the network card of server and avoid bandwidth contesting between them. Experimental results show that the proposed system can mitigate the quality degradation of video streaming due to the fluctuations of time-varying channel and simultaneously support 33-channel HDTV streams. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel shape descriptor for 3D objects, called spatial geometric descriptor (SGD), to represent the spatial geometric information of a 3D model by mapping its furthest distance, normal and area distribution onto spherical grids in a sequence of concentric shells. Then these spherical distribution functions are transformed to spherical harmonic coefficients which not only save the storage space but also provide multi-resolution shape description for any 3D model by adopting different dimensions for the coefficients. The feature vector extraction time can be reduced by adopting a single scan scheme on the mesh surface for a given 3D model. The retrieval performance is evaluated on the public Princeton Shape Benchmark (PSB) dataset and the experimental results show that our method not only outperforms Light Field Descriptor which is regarded as the best shape descriptor so far but also maintains an advantage of fast feature vector extraction procedure. [ABSTRACT FROM AUTHOR]

Active Appearance Model is a well-known model that can represent a non-rigid object effectively. However, since it uses the fixed appearance model, the fitting results are often unsatisfactory when the imaging condition of the target image is different from that of training images. To alleviate this problem, incremental AAM was proposed which updates its appearance bases in an on-line manner. However, it can not deal with the sudden changes of illumination. To overcome this, we propose a novel scheme to update the appearance bases. When a new person appears in the input image, we synthesize illuminated images of that person and update the appearance bases of AAM using it. Since we update the appearance bases using synthesized illuminated images in advance, the AAM can fit their model to a target image well when the illumination changes drastically. The experimental results show that our proposed algorithm improves the fitting performance over both the incremental AAM and the original AAM. [ABSTRACT FROM AUTHOR]

We investigate the problem of automatically identifying speaking faces for video analysis using only the visual information. Intuitively, mouth should be first accurately located in each face, but this is extremely challenging due to the complicated condition in video, such as irregular lighting, changing face poses and low resolution etc. Even though we get the accurate mouth location, it's still very hard to align corresponding mouths. However, we demonstrate that high precision can be achieved by aligning mouths through face matching, which needs no accurate mouth location. The principal novelties that we introduce are: (i) proposing a framework for speaking face identification for video analysis; (ii) detecting the change of the aligned mouth through face matching; (iii) introducing a novel descriptor to describe the change of the mouth. Experimental results on videos demonstrated that the proposed approach is efficient and robust for speaking face identification. [ABSTRACT FROM AUTHOR]

In many rate control models, a uniform weighted distortion has been assumed; that is, the DCT coefficients of the motion-compensation difference frames (residues) conform to a uniform distribution. However, the residue after transform does not conform to a uniform distribution but approximate to a Laplacian distribution. In this paper, we first deduce a new distortion model with the assumption of Laplacian distribution of quantized DCT coefficients (called Laplacian distortion model, LDM), and then a more accurate rate-distortion model is proposed based on LDM. Experimental results on H.264/AVC show that our proposed method can improve PSNR up to 0.8dB compared to that of traditional TMN8; meanwhile, the mismatch of target bit rate and actual bit rate generated for coding can be controlled below 2.5%. [ABSTRACT FROM AUTHOR]

The two-dimensional Principal Component Analysis (2DPCA) is a robust method in face recognition. Much recent research shows that the 2DPCA is more reliable than the well-known PCA method in recognising human face. However, in many cases, this method tends to be overfitted to sample data. In this paper, we proposed a novel method named random subspace two-dimensional PCA (RS-2DPCA), which combines the 2DPCA method with the random subspace (RS) technique. The RS-2DPCA inherits the advantages of both the 2DPCA and RS technique, thus it can avoid the overfitting problem and achieve high recognition accuracy. Experimental results in three benchmark face data sets − the ORL database, the Yale face database and the extended Yale face database B − confirm our hypothesis that the RS-2DPCA is superior to the 2DPCA itself. [ABSTRACT FROM AUTHOR]

Previous work has shown that human faces under variable lighting conditions can be modeled by low-dimensional subspaces called illumination subspaces that can be computed using images under a universal lighting configuration. This configuration can be estimated using Harmonic images. However, harmonic images can only be obtained by using 3D information, and thus can be restrictive. In this paper, we overcome this limitation by presenting a completely data-driven method to find good universal lighting configurations. Motivated by the fact that affinity propagation clustering finds the cluster centers from the real images, we use affinity propagation clustering on real images taken under variable lighting conditions to find the cluster centres and use them to determine the lighting configuration. The illumination subspace for each individual is spanned by their images acquired in this lighting configuration. Matching is performed by comparing the distances to these individual illumination subspaces. Further, kernel methods are used to explore the non-linear structures of the illumination cone and carry out the illumination subspace methods in the kernel induced feature space. Experiments conducted on the Extended Yale Face B database demonstrate that the configuration obtained by our method is better than earlier recommended configurations. We also demonstrate that our technique is robust to pose variations using the CMU PIE database. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of quality control for distributed video coding (DVC). In a pure DVC framework, the compression performance conflicts with the consistency of the video quality. A hybrid framework is proposed to solve this problem. Wyner-Ziv video coding and zero vector motion compensation are combined to keep the visual quality in consistency while maintaining satisfied compression efficiency. Simulation results show that the proposed framework can effectively reduce the variance of the video quality, and the compression performance is 1-5dB better than pure DVC framework worked in constant quality mode. We also evaluate the decoding efficiency of two multistage decoding (MSD) strategies in Wyner-Ziv coding. Simulate results show that passing soft decision from low level to high level works better in DVC. [ABSTRACT FROM AUTHOR]

In this work, we investigate error patterns in compressed multi-view video signals and propose three error concealment algorithms, which can hide the effects of transmission errors efficiently. The proposed algorithms conceal a lost block by choosing and combining the best candidate blocks in the temporally adjacent frames or the inter-view frames at the same time instance. Simulation results demonstrate that the proposed algorithms effectively protect the quality of reconstructed videos against transmission errors. [ABSTRACT FROM AUTHOR]

We propose a novel news browsing system that can cluster photo news articles based on both textual features of articles and image features of news photos for a personal news database which is built by accumulating Web photo news articles. The system provides two types of clustering methods: normal clustering and thread-style clustering. It enables us to browse news articles over several weeks or months visually and find out useful news easily. In this paper, we describe an overview of our system, some examples of uses and user studies. [ABSTRACT FROM AUTHOR]

In this paper, we propose a parallel algorithm for H.264/AVC intra frame encoding by using the graphics processing unit (GPU). The proposed algorithm can handle 4x4 intra block prediction and reconstruction. By rearranging the encoding order of 4x4 blocks and modifying the architecture of H.264/AVC encoder, thirty times speed up can be achieved which utilizing the computing power of GPU without any loss in coding efficiency. [ABSTRACT FROM AUTHOR]

Intra video coding is a common way to process video material for applications like professional video editing systems, digital cinema, video surveillance applications, multispectral satellite imaging, HQ video delivery, etc. Most practical intra coding systems employ JPEG encoders due to their simplicity, low coding delay and low memory requirements. JPEG2000 is the main candidate to replace JPEG in this kind of applications due to the excellent R/D performance and high coding flexibility. However, its complexity and computational resources required for proper operation could be a limitation for certain applications. In this work, we propose an intra video codec, M-LTW, which is able to reach very good R/D performance results, as well as JPEG2000 or H.264 INTRA, with faster processing and lower memory usage. [ABSTRACT FROM AUTHOR]

A Body Area Network (BAN) is a body worn system which provides the user with a set of mobile services. A BAN incorporates a set of devices (eg. mp3 player, video camera, speakers, microphone, head-up display, positioning device, sensors, actuators). A BAN service platform for mobile healthcare and several health BANs targetting different clinical applications have been developed at the University of Twente. Each specialization of the BAN is equipped with a certain set of devices and associated application components, as appropriate to the clinical application. Different kinds of clinical data may be captured, transmitted and displayed, including text, numeric values, images and multiple biosignal streams. Timely processing and transmission of such multimedia clinical data in a distributed mobile environment requires smart strategies. Here we present one approach to designing smart distributed applications to deal with multimedia BAN data; namely the context awareness approach developed in the FREEBAND AWARENESS project. [ABSTRACT FROM AUTHOR]

Implementing reliable Video on Demand (VoD) systems over the Internet, which is inherently best-effort, is a challenge. Distributed streaming for Video on Demand addresses this challenge with a combination of two techniques. The first, Distributed Video Streaming using Multicast (DVSM) involves video streaming from multiple servers to overcome path congestion by exploiting path diversity. The second technique, Asynchronous Hybrid mechanism for Video on Demand, implements a segmentation-based periodic broadcast to effectively utilize network bandwidth and decrease latency. The combination involves devising new algorithms for bandwidth estimation, segment partitioning and scheduling. A simulation of our proposed solution demonstrates its effectiveness. Specifically the results show, the prompt reaction of our strategy to congestion, and, the effect the various parameters have on system performance. The results shed light on parameters that can be fine-tuned for an effective VoD system. [ABSTRACT FROM AUTHOR]

Streaming media has contributed to a significant amount of today's Internet Traffic. One solution of to solve this problems is using streaming proxy. There are two categories in streaming proxy; that is for homogeneous and heterogeneous client. The transcoding proxy can be used for heterogeneous client. The traditional proxy considers only a single version of the objects, whether they are to be cached or not. However the transcoding proxy has to evaluate the aggregate effect from caching multiple versions of the same object to determine an optimal set of cache objects. And recent researches about multimedia caching frequently store initial parts of videos on the proxy to reduce playback latency and archive better performance. Also lots of researches manage the contents with segments for efficient storage management. In this paper, we propose the efficient proxy policy that combines the segment-based caching mechanism and aggregate effect at transcoding proxy. The results demonstrate that the proposed algorithm outperforms in delay time, byte-hit ratio and the amount of transcoding data than other methods. [ABSTRACT FROM AUTHOR]

H.264/AVC is the newest international video coding standard. This paper presents a novel hardware design for CABAC decoding in H.264/AVC. CABAC is the key innovative technology, but it brings huge challenge for high throughput implementation. The current bin decoding depends on the previous bin, which results in the long latency and limits the system performance. In this paper, the data hazards are analyzed and resolved using the algorithmic features. We present a new pipeline-based architecture using the standard look-ahead technique where the arithmetic decoding engine works in parallel with the context maintainer. An efficient finite state machine is developed to match the requirement of the pipeline controlling and the critical path is optimized for the timing. The proposed implementation can generate one bin per clock cycle at the 160-MHz working frequency. [ABSTRACT FROM AUTHOR]

Within an MPEG-21 architecture, the two key concepts are the Digital Item, representing multimedia content, and Users, interacting with this content. MPEG-21 introduced Digital Item Processing to allow content authors to describe suggested processing of their Digital Items. It standardizes ways to insert functionality into a Digital Item, as such, creating a dynamic and interactive multimedia format. Moreover, if a terminal wants to support Digital Item Processing, it needs to provide an execution environment offering basic functionality. The semantics of this functionality have been standardized, however there is significant room for interpretation. Consequently, a Digital Item author may not be aware of the actual processing when using this functionality. In this paper, a system is proposed, compliant with the Digital Item Processing specification, to give content creators full control on the processing. This allows creating advanced predictable multimedia systems in an MPEG-21 environment. [ABSTRACT FROM AUTHOR]

In this paper, audio data-hiding schemes and speaker/recorder devices are employed to deliver information within nearby areas where connection and networking capabilities are expensive or even unavailable. Conventionally, information delivery in this way suffers from low data rate, questionable robustness and, most seriously, the limited transmission distance. Here, we alleviate the constraint of short transmission distance by devising a novel application scenario where widely available speaker/recorder devices move around together with the recipient - the information delivery service based on car radio systems. To be more specific, passengers in cars can receive additional visual information broadcasted through radio channels using devices capable of audio recording. To achieve sufficient data rate and necessary robustness, existing audio watermarking schemes have been enhanced. Furthermore, empirical on-road tests are performed to evaluate the robustness of the proposed scheme in real-world environments. According to our experimental results, enhanced audio watermarking schemes can be practically adopted to provide visual information without introducing additional costs or specific receivers in the client end. The proposed scheme can bring new business opportunities and commercial values for existing radio channels and car radio systems. [ABSTRACT FROM AUTHOR]

In this paper, we propose an Error Concealment algorithm for INTRA-frame losses over packet loss channels. The novelty is that not only the INTRA-frame but also the subsequent INTER-frames are error concealed. We use the received INTRA-MBs to refine their neighbors based on the strong correlation between adjacent pixel values. In addition, Motion Compensation is used to reconstruct the INTER-pixel which has an INTRA-pixel in its motion trajectory. Both subjective and objective simulation results are given to demonstrate the performance of our proposed algorithm. [ABSTRACT FROM AUTHOR]

The integration of scalable video representation and network coding (NC) offers an excellent solution to robust and flexible video multicast over IP networks. In this work, we examine one critical component in this system, i.e. video priority ordering and packetization at the source of the multicast tree. First, a GOP-adaptive layer-based packet priority ordering algorithm is proposed to allow flexible prioritized video transmission with unequal error protection. Then, a packetization scheme tailored to NC delivery is discussed. Simulation results are given to demonstrate that the proposed algorithms offer better performance in video quality and bandwidth efficiency as compared the SNR-based packetization method. [ABSTRACT FROM AUTHOR]

A new challenge to data visualization has arisen from a new laboratory technique that is capable of imaging a large number of biomedical relevant molecule types in a single tissue probe, termed the Toponome. While aiming at deciphering the biochemical interactions of the molecules, and thus their biological functions as well their roles in diseases, no current methods of image analysis are fully suited for this new quality of high-dimensional image data. To overcome this problem we demonstrate a novel framework for interactive real-time visualization, making use of standard graphics acceleration hardware. We show a sample implementation of a threshold-based visualization technique that is connected to the original work of the Toponome authors, improving it by means of fast user interaction. [ABSTRACT FROM AUTHOR]

Biomedicine is a very rich field of multimedia information. It is also a fruitful ground for information fusion and integration about scientific research data as well as clinical records of digital medical systems. In this paper, we present a global overview of these ideas, which have not been realized so far and could be interesting to the multimedia research community. We exemplify the complex information resources in terms of Gene Ontology (GO), Clinical Bioinformatics Ontology (CBO) and the Foundational Model of Anatomy (FMA). GO is a biomedical scientific research system used to describe genes and gene products, but no cellular components. CBO is a clinical oriented ontology of information, which potentially include many multimedia images: X-Ray, ultrasound and magnetic resonance images. FMA is a foundational clinical source used to describe the anatomy of the human body as well as cellular components. While scientists in each sector may use these systems to help develop their own information, it is very difficult for a layman or broad-spectrum researcher to integrate the two different languages into one interface. We will attempt to address these issues to describe how information fusion can be achieved. [ABSTRACT FROM AUTHOR]

Orthogonal Frequency Division Multiplexing (OFDM) is a promising technique in broadband wireless communication systems. This paper presents a novel multi-reference scheme based on 3D interleaving for video coding and transmission over OFDM channel. Initially, a combining interleaving method in spatial, frequency and temporal domains, called SFTI, is proposed. With SFTI, different slices within one frame are transmitted in different sub-channels of OFDM, whose SNR can be estimated, and the transmission status of slices through these sub-channels are real-time feedback to the encoder. Based on the feedback information, a multi-reference scheme for video coding is proposed where the well-transmitted slices are selected as the reference picture of its consequent pictures in inter-frame coding to eliminate the impairment caused by error propagation in video transmission over wireless OFDM channels. Extensive experimental results have demonstrated the effectiveness of the proposed methods in error resilience. [ABSTRACT FROM AUTHOR]

Time lapse video microscopy routinely produces terabyte sized biological image sequence collections, especially in high throughput environments, for unraveling cellular mechanisms, screening biomarkers, drug discovery, image-based bioinformatics, etc. Quantitative movement analysis of tissues, cells, organelles or molecules is one of the fundamental signals of biological importance. The accurate detection and segmentation of moving biological objects that are similar but non-homogeneous is the focus of this paper. The problem domain shares similarities with multimedia video analytics. The grayscale structure tensor fails to disambiguate between stationary and moving features without computing dense velocity fields (i.e. optical flow). In this paper we propose a novel motion detection algorithm based on the flux tensor combined with multi-feature level set-based segmentation, using an efficient additive operator splitting (AOS) numerical implementation, that robustly handles deformable motion of non-homogeneous objects. The flux tensor level set framework effectively handles biological video segmentation in the presence of complex biological processes, background noise and clutter. [ABSTRACT FROM AUTHOR]

This paper proposes a kind of remote rendering method based on awareness model. This method takes the additional cost caused by the movement of the viewpoint into cost calculation and designs a cost prediction algorithm based on the vision field divided by awareness model. The simulation results show that the improved method can not only improve the quality of the remote rendering, but also make full use of the bandwidth of the network, as well as make the remote rendering more fluent when the viewpoint moves fast. [ABSTRACT FROM AUTHOR]

We propose an intrinsic-distance based segmentation approach for segmenting human body parts in video frames. First, since the human body can be seen as a set of articulated parts, we utilize the moving articulated attributes to identify body part candidate regions automatically. The candidate regions and the background candidate regions are generated by voting and assigned to the spatiotemporal volume, which is comprised of frames of the video. Then, the intrinsic distance is used to estimate the boundaries of each body part. Our intrinsic distance-based segmentation technique is applied in the spatiotemporal volume to extract the optimal boundaries of the intrinsic distance in a video and obtain segmented frames from the segmented volume. The segmented results show that the proposed approach can tolerate incomplete and imprecise candidate regions because it provides temporal continuity. Furthermore, it can reduce over growing in the original intrinsic distance-based algorithm, since it can handle ambiguous pixels. We expect that this research can provide an alternative to segmenting a sequence of body parts in a video. [ABSTRACT FROM AUTHOR]

A low complexity video de-interlacing algorithm is presented in this paper which is suitable for SIMD (Single Instruction Multiple Data) processors to be used as a pre-/post-processing option in low-cost consumer electronic devices. It is a block-based motion-adaptive technique that converts an interlaced video to progressive, preserving the details in static or low motion areas while leaving no combing artifacts or without introducing any ghosting artifacts. It adapts to the content and chooses one amongst temporal, spatio-temporal or spatial filtering for de-interlacing on a block by block basis analyzing characteristics such as the extent of motion and the correlation across fields. The proposed scheme has been benchmarked against a recent low complexity motion-adaptive algorithm and the performance has been measured across a number of real and synthetic video sequences. The proposed algorithm offers an order of magnitude complexity reduction on SIMD processors over the reference low complexity algorithm while providing a significantly better fidelity towards the progressive source. [ABSTRACT FROM AUTHOR]

In this paper, an efficient video watermarking scheme is presented through modifying the third decoded luminance differential DC component in each selected macro block. The modification is implemented by binary dither modulation with adaptive quantization step. The proposed scheme is based on the observation that luminance differential DC components inside one macro block are generally space correlated, so the quantization step can be adjusted according to adjacent differential components, to utilize properties of human visual system (HVS). This method is very robust to gain attacks since amplitude scaling will have the same effect on differential components and the quantization step. Experimental results show that it can be implemented in real time with better visual quality than uniform-quantizing scheme. [ABSTRACT FROM AUTHOR]

A blind image watermarking scheme based on secret sharing in discrete wavelet transform domain is proposed. Watermark was divided into n shadows according to secret sharing scheme. And t or more of those shadows can reconstruct the watermark, while t-1 or less shadows could not do it. In order to achieve optimum embedding strategy, a closed loop embedding process is proposed, which is modified iteratively according to results of performance analysis. The convergence of closed loop watermarking is proved. Independent component analysis is utilized so that detector can not merely detect watermark but also can extract it. Before watermark reconstruction, one way hashing function is used to withstand cheating attacks. The experimental results show that it is robust against a wide range of attacks proposed by Stirmark and it is more safety than traditional watermarking techniques. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the text extraction of image, and propose a new approach for it into two phases: Firstly, for the effective binarization of text region image, instead of performing the binarization in a constant color plane as in the existing methods, our approach adaptively selects the relatively best color plane for the binarization, which uses the text contrast difference among the color planes. Secondly, to remove the noise in the binary image, we consider the color difference between the text strokes and noises, and the color-based clustering is then utilized to remove the noise for the effective text recognition. The experimental result has shown that the proposed approach is better than the existing methods in terms of the performance of text extraction. [ABSTRACT FROM AUTHOR]

We present an image authentication scheme based on feature extraction and codeword clustering in this paper. The two-level detections can be performed progressively based on the requirements of the authenticator. In order to generate these two-level authentication codes, the quad-tree segmentation and clustered VQ techniques are used. Using the first-level authentication code, the malicious tampered areas can be detected and located. In the second-level, it not only provides a more rigid detection of tampered areas but also can further remedy them. According to the experimental results, our scheme can correctly detect the malicious tampering and tolerate some incidental modifications, and then successfully remedy the tampered area. In addition, the space cost of authentication code is quite little. [ABSTRACT FROM AUTHOR]

Temporal attacks will affect temporal synchronization signals loss. In this paper, we propose a low complexity temporal synchronization recovery method using local variance statistics in each group of picture (GOP), which is regarded as the feature parameters and sent as side information to recover synchronization signals. The temporal distortions can be identified by comparision of the feature parameters and the feature statistics of the received watermarked video data. Simulation results show that the proposed method is more robust against temporal attacks. [ABSTRACT FROM AUTHOR]

We propose a novel block-based symmetric encryption system based on an n-array of independently iterated chaotic logistic maps with global and local feedback as a diffusion process. Local feedback represents the temporal evolution of a single map, while global feedback represents the temporal evolution of the whole system (cross-map evolution). For security, the cryptosystem periodically modifies its internal configuration using a three-level random perturbation scheme, one at system-key (reset operation) and two at map array level (to increase the chaotic cycle length of the system). An analysis of the proposed scheme regarding its vulnerability to attacks, statistical properties and implementation performance is presented. To the best of our knowledge we provide a simple and secure scheme with the fastest software implementation reported in the literature. [ABSTRACT FROM AUTHOR]