We describe PRISM, a video coding paradigm based on the principles of lossy distributed compression (also called source coding with side information or Wyner-Ziv coding) from multiuser information theory. PRISM represents a major departure from conventional video coding architectures (e.g., the MPEGx, H.26x families) that are based on motion-compensated predictive coding, with the goal of addressing some of their architectural limitations. PRISM allows for two key architectural enhancements: (1) inbuilt robustness to "drift" between encoder and decoder and (2) the feasibility of a flexible distribution of computational complexity between encoder and decoder. Specifically, PRISM enables transfer of the computationally expensive video encoder motion-search module to the video decoder. Based on this capability, we consider an instance of PRISM corresponding to a near reversal in codec complexities with respect to today's codecs (leading to a novel light encoder and heavy decoder paradigm), in this paper. We present encouraging preliminary results on real-world video sequences, particularly in the realm of transmission losses, where PRISM exhibits the characteristic of rapid recovery, in contrast to contemporary codecs. This renders PRISM as an attractive candidate for wireless video applications.

PRISM: A Video Coding Paradigm With Motion Estimation at the Decoder

The technological advances in Micro ElectroMechanical Systems (Mems) and wireless communications have enabled the realization of wireless sensor networks (Wsn) comprised of large number of low-cost, low-power, multifunctional sensor nodes These tiny sensor nodes communicate in short distances and collaboratively work toward fulfilling the application specific objectives ofWsn However, realization of wide range of envisionedWsn applications necessitates effective communication protocols which can address the unique challenges posed by theWsn paradigm Since many of these envisioned applications may also involve in collecting information in the form of multimedia such as audio, image, and video; additional challenges due to the unique requirements of multimedia delivery overWsn, eg, diverse reliability requirements, time constraints, high bandwidth demands, must be addressed as well Thus far, vast majority of the research efforts has been focused on addressing the problems of conventional data communication inWsn Therefore, there exists an urgent need for research on the problems of multimedia communication inWsn In this paper, a survey of the research challenges and the current status of the literature on the multimedia communication inWsn is presented More specifically, the multimediaWsn applications, factors influencing multimedia delivery overWsn, currently proposed solutions in application, transport, and network layers, are pointed out along with their shortcomings and open research issues

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Multimedia communication in wireless sensor networks

Intelligent motion capture element that includes sensor personalities that optimize the sensor for specific movements and/or pieces of equipment and/or clothing and may be retrofitted onto existing equipment or interchanged therebetween and automatically detected for example to switch personalities. May be used for low power applications and accurate data capture for use in healthcare compliance, sporting, gaming, military, virtual reality, industrial, retail loss tracking, security, baby and elderly monitoring and other applications for example obtained from a motion capture element and relayed to a database via a mobile phone. System obtains data from motion capture elements, analyzes data and stores data in database for use in these applications and/or data mining. Enables unique displays associated with the user, such as 3D overlays onto images of the user to visually depict the captured motion data. Enables performance related equipment fitting and purchase. Includes active and passive identifier capabilities.

Intelligent motion capture element

A method and system acquire and display light fields. A continuous light field is reconstructed from input samples of an input light field of a 3D scene acquired by cameras according to an acquisition parameterization. The continuous light is reparameterized according to a display parameterization and then prefiltering and sampled to produce output samples having the display parametrization. The output samples are displayed as an output light field using a 3D display device. The reconstruction can be performed by interpolating the input samples having the different views.

Method and System for Acquiring, Encoding, Decoding and Displaying 3D Light Fields

This paper addresses the important aspect of compressing and transmitting video signals generated by wireless broadband networks while heeding the architectural demands imposed by these networks in terms of energy constraints as well as the channel uncertainty related to the wireless communication medium. Driven by the need to develop light, robust, energy-efficient, and low delay video delivery schemes, a distributed video coding based framework dubbed PRISM is introduced. PRISM addresses the wireless video sensor network requirements far more effectively than current state-of-the-art standards like MPEG. This paper focuses on the case of a single video camera and use it as a platform to describe the theoretical principles and practical aspects underlying distributed video coding.

Distributed video coding in wireless sensor networks

Golf Club Visual Tracking for Enhanced Swing Analysis Tools

We address the problem of distributed compression in camera sensor networks. Our approach uses some geometrical information in order to estimate the correlation in the visual data. This correlation, which is related to the structure of the plenoptic function, can then be used to reduce the overall transmission rate from the sensors to a common central receiver. Our approach allows for a flexible allocation of the bit-rates amongst the encoders and can be made resilient to a fixed number of occlusions. Finally, we show that our distributed coding approach can be extended to general binary sources. The technique we propose uses linear channel codes and can achieve any point of the Slepian-Wolf achievable rate region.

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Distributed compression in camera sensor networks

In this paper, we propose a practical coding approach for the problem of distributed compression of multi-view images. Our coding technique is based on a tree structured compression algorithm that guarantees an optimal rate-distortion behaviour for piecewise polynomial signals. We model the different views using a piecewise polynomial function whose singularity positions are shifted from one view to the others according to the constraints imposed by the structure of the plenoptic function. We show that, starting from the optimal tree decompositions of the different views, only partial information from each tree is necessary at the decoder in order to reconstruct all the different approximations. We first present our approach in the more intuitive 1D case and show that it can be used with arbitrary bit-rate allocation. Then, we propose a construction for the case of TV different views that satisfies a certain bit conservation principle. Finally, we show how our approach can be extended to the 2D case.

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Dfferent - distributed and fully flexible image encoders for camera sensor networks

In this paper, we study the sampling and the distributed compression of the data acquired by a camera sensor network. The effective design of these sampling and compression schemes requires, however, the understanding of the structure of the acquired data. To this end, we show that the a priori knowledge of the configuration of the camera sensor network can lead to an effective estimation of such structure and to the design of effective distributed compression algorithms. For idealized scenarios, we derive the fundamental performance bounds of a camera sensor network and clarify the connection between sampling and distributed compression. We then present a distributed compression algorithm that takes advantage of the structure of the data and that outperforms independent compression algorithms on real multiview images.

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Geometry-Driven Distributed Compression of the Plenoptic Function: Performance Bounds and Constructive Algorithms

In this paper, we propose a distributed compression approach for multi-view images, where each camera efficiently encodes its visual information locally without requiring any collaboration with the other cameras. Such a compression scheme can be necessary for camera sensor networks, where each camera has limited power and communication resources and can only transmit data to a central base station. The correlation in the multi-view data acquired by a dense multi-camera system can be extremely large and should therefore be exploited at each encoder in order to reduce the amount of data transmitted to the receiver. Our distributed source coding approach is based on a quadtree decomposition method and uses some geometrical information about the scene and the position of the cameras to estimate this multi-view correlation. We assume that the different views can be modelled as 2D piecewise polynomial functions with ID linear boundaries and show how our approach applies in this context. Our simulation results show that our approach outperforms independent encoding of real multi-view images.

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N. Gehrig

Papers

Golf Club Visual Tracking for Enhanced Swing Analysis Tools

Distributed compression in camera sensor networks

Dfferent - distributed and fully flexible image encoders for camera sensor networks

Geometry-Driven Distributed Compression of the Plenoptic Function: Performance Bounds and Constructive Algorithms

Distributed Compression of Multi-View Images using a Geometrical Coding Approach