Research Activities

The main goal of the TEMICS project is the design and development of theoretical framework as well as algorithms and practical solutions in the areas of analysis, modelling, coding, communication, and watermarking of images and video signals. TEMICS activities are structured and organized around the following research directions:

Analysis and modelling of video sequences

The support of advanced interaction functionalities, such as video content manipulation, or navigation requires the development of video analysis and modelling algorithms. TEMICS focuses on the design of solutions for segmenting video objects and for extracting and coding their main attributes (shape, motion, illumination, ...). In order to support navigation within video scenes, the ability to construct a 3d model of the scene is a key issue. One specific problem addressed is the design of algorithms for 3d modelling from monocular video sequences with optimum tradeoff between model reliability and description cost (rate). Finally, the optimal support of the above functionalities in networked multimedia applications requires scalable, compact and transmission noise resilient representations of the models and of their attributes, making use of joint source-channel coding principles.

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Joint source-channel coding

The advent of Internet and wireless communications, often characterised by narrow-band, error and/or loss prone, heterogeneous and time-varying channels, is creating challenging problems in the area of source and channel coding. Design principles prevailing so far and stemming from Shannon's source and channel separation theorem must be re-considered. The separation theorem, stating that source and channel optimum performance bounds can be approached as close as desired by designing independently source and channel coding strategies, holds only under asymptotic conditions where both codes are allowed infinite length and complexity. If the design of the system is heavily constrained in terms of complexity or delay, source and channel coders, designed in isolation, can be largely suboptimal.

The project objective is to develop a theoretical and practical framework setting the foundations for optimal design of image and video transmission systems over heterogeneous, time-varying wired and wireless networks. Many of the theoretical challenges are related to understanding the tradeoffs between rate-distortion performance, delay and complexity for the code design. The issues addressed encompass the design of errorresilient source codes, joint source-channel source codes and multiply descriptive codes, minimizing the impact of channel noise (packet losses, bit errors) on the quality of the reconstructed signal, as well as of turbo or iterative decoding techniques in order to address the tradeoff performance-complexity.

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Compression, scalable coding and distributed source coding

Scalable video compression is essential to allow for optimal adaptation of compressed video streams to varying network characteristics (e.g. to bandwidth variations) in various applications (e.g. in unicast streaming applications with pre-encoded streams, and in multicast applications). Frame expansions and in particular wavelet-based signal representations are well suited for such scalable signal representations. Special effort is thus dedicated to the study of motion-compensated spatio-temporal expansions making use of complete or overcomplete transforms, e.g. wavelets, curvelets and contourlets.

Current compression systems exploit correlation on the sender side, via the encoder, e.g. making use of motion-compensated predictive or filtering techniques. This results in asymmetric systems with respectively higher encoder and lower decoder complexities suitable for applications such as digital TV, or retrieval from servers with e.g. mobile devices. However, there are numerous applications such as multi-sensors, multi-camera vision systems, surveillance systems, light-weight video compression systems (extension of MMS-based still image transmission to video) that would benefit from the dual model where correlated signals are coded separately and decoded jointly. This model, at the origin of distributed source coding, finds its foundations in the Slepian-Wolf theorem established in 1973. Even though first theoretical foundations date back to early 70s, it is only recently that concrete solutions, motivated by the above applications, aiming at approaching the theoretic performance bounds have been introduced.

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Data hiding and watermarking

The distribution and availability of digital multimedia documents on open environments, such as the Internet, has raised challenging issues regarding ownership, users rights and piracy. With digital technologies, the copying and redistribution of digital data has become trivial and fast, whereas the tracing of illegal distribution is difficult. Consequently, content providers are increasingly reluctant to offer their multimedia content without a minimum level of protection against piracy. The problem of data hiding has thus gained considerable attention in the recent years as a potential solution for a wide range of applications encompassing copyright protection, authentication, and steganography. However, data hiding technology can also be used for enhancing a signal by embedding some meta-data.

The data hiding problem can be formalized as a communication problem : the aim of robust data hiding is indeed to embed the maximum amount of information in a host signal, under a fixed distortion constraint between the original and the watermarked signal, while at the same time allowing reliable recovery of the embedded information subject to a fixed attack distortion. Our developments rely on this formalism, i.e., on scientific foundations in the areas of communication theory, such as channel coding with side information and joint source-channel coding concepts and algorithms.

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Last time modified: 2006-03-02