Program supervision techniques for easy configuration of video understanding systems

The context of this thesis is the semantic understanding of video sequences. Semantic video understanding is here defined as the task of recognition of predefined event models in a given application domain (e.g., human activities) starting from a pixel analysis up to a symbolic description of what is happening in the scene viewed by cameras. Although various approaches and techniques have already been proposed for understanding video sequences, this task remains a complex problem regarding the lack of performances when facing challenging environments (e.g., a cluttered scene) and the lack of reusability when a system has to be deployed on a large scale with minimum human interventions. In this context, this thesis proposes a complete framework to conceive supervised video understanding platforms. Such platforms are used to easily create and configure video understanding systems. Several issues need to be addressed to provide a correct configuration: (1) the ability to choose, among a library of programs, those which are best satisfying a given request, (2) the ability to dynamically adapt programs and parameters to situation changes, (3) the ability to evaluate performances and to guarantee continuously a maximum performance rate which is satisfactory regarding end-user requirements. We propose a knowledge-based approach for the supervision of video processing programs in order to externalize both the control and the knowledge of programs. We propose a model for program control which is generic in the sense that it is independent of any application. The need of having a formalism for knowledge representation is demonstrated for each type of knowledge: knowledge of the application domain, knowledge of the scene environment and knowledge of video processing programs. In addition, the framework provides a methodology for the evaluation of system performances. This methodology proposes a video sequence characterization which guides the selection of video sequences which are used for testing a system. In order to perform the evaluation, the methodology also proposes a set of metrics to compare results with reference data. Thanks to this evaluation methodology, video processing experts are able to acquire expertise on the use of programs. Finally, the framework allows the use of learning techniques where knowledge is hardly available. The proposed framework has been validated on a video understanding platform. Thanks to this supervised platform, we have created six systems in a few amount of time. These systems are characterized by four properties: adaptability, reusability, effectiveness and real-time processing.Doctorat en sciences appliquées (FSA 3)--UCL, 200

Towards an Evaluation and Repair Framework for Video Interpretation

This report is laid out as follows. Chapter 2 browses existing evaluation processes 6 and briefly describes program supervision techniques which guide our work. Our video interpretation platform is explained and illustrated in chapter 3. Chapter 4 describes the evaluation process, preceded by a video input characterization, a description of the ground truth generation and a definition of the results criteria. Chapter 5 details the global evaluation algorithm and discusses the results obtained, both for mobile object detection and tracking. Chapter 6 explains how we refined this global evaluation algorithm in the tracking case. We conclude this chapter by describing the repair methodology using this fine evaluation. Chapter 7 draws the conclusion of this work. Finally, chapter 8 indicates further work which is composed of two main research axes, the first one being the automatization of evaluation and repair and the second one being the generalization of the evaluatio

Combined line-based architecture for the 5-3 and 9-7 wavelet transform of JPEG2000

The wavelet transform is a very promising tool for image compression. In JPEG2000, two filter banks are used, one an integer lossless 5-3 filter, and one a lossy 9-7. A combined architecture for the 5-3 and 9-7 transforms with minimum area is presented in this paper. The lifting scheme is used to realize a fast wavelet transform. Two lines are processed at a time. This line-based architecture allows minimum memory requirement and fast calculation. The pipeline and the optimization of the operations provide speed, while the combination of the two transforms in one structure contributes to saving the area. On a VIRTEXE1000-8, de coding of 2 pixels per clock cycle can be performed at 110 MHz. Only 19% of the total area of the VIRTEXE1000 is needed. Compared to existing architectures, memory resource and area can be reduced thanks to the solution proposed in this paper

Inorganic arsenic methylation by rat tissue slices.

Rat liver, kidney and lung slices methylate trivalent inorganic arsenic (AsIII) to monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA); the liver has the greatest methylating capacity. AsIII enters the liver cells by a diffusion process followed by extensive binding to intracellular components which favors its extensive accumulation inside the cells. Reduced glutathione regulates AsIII metabolism through several mechanisms: facilitation of AsIII diffusion into the cells, stimulation of the first methylation reaction and increase of DMA excretion by the cells. An excess of AsIII inhibits DMA production by liver cells but this inhibition is reversible; mercuric ions inhibit both MMA and DMA production probably by decreasing inorganic arsenic (Asi) uptake and the second methylation reaction. DMA can be produced from MMA by rat liver slices and this methylation step is stimulated by GSH. In contrast to AsIII, AsV is not extensively taken up by the hepatocyte and is thus poorly methylated

Using team debriefing for critical care humanization: a quality improvement initiative at the University Hospital of Liège.

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