Ewa Kijak

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This paper focuses on the integration of multimodal features for sport video structure analysis. The method relies on a statistical model which takes into account both the shot content and the interleaving of shots. This stochastic modelling is performed in the global framework of Hidden Markov Models (HMMs) that can be efficiently applied to merge audio(More)
This paper focuses on the use of Hidden Markov Models (HMMs) for structure analysis of videos, and demonstrates how they can be efficiently applied to merge audio and visual cues. Our approach is validated in the particular domain of tennis videos. The basic temporal unit is the video shot. Visual features are used to characterize the type of shot view.(More)
This work aims at recovering the temporal structure of a broadcast tennis video from an analysis of the raw footage. Our method relies on a statistical model of the interleaving of shots, in order to group shots into predefined classes representing structural elements of a tennis video. This stochastic modeling is performed in the global framework of Hidden(More)
Content-Based Image Retrieval Systems (CBIRS) used in forensics related contexts require very good image recognition capabilities. Whereas the robustness criterion has been extensively covered by Computer Vision or Multimedia literature , none of these communities explored the security of CBIRS. Recently, preliminary studies have shown real systems can be(More)
Many content-based retrieval systems (CBIRS) describe images using the SIFT local features because of their very robust recognition capabilities. While SIFT features proved to cope with a wide spectrum of general purpose image distortions, its security has not fully been assessed yet. In one of their scenario, Hsu <i>et al.</i> in [2] show that very(More)
The benchmarking of various methods of video analysis and indexing has become a research problem per se. The Argos evaluation campaign supported by the French Techno-Vision program aimed at developing resources for a benchmarking of video content analysis and indexing methods. The paper describes the type of the evaluated tasks, the way the content set has(More)
We present a new, block-based image codec based on sparse representations using a learned, structured dictionary called the Iteration-Tuned and Aligned Dictionary (ITAD). The question of selecting the number of atoms used in the representation of each image block is addressed with a new, global (image-wide), rate-distortion-based sparsity selection(More)