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We propose a new measurement of video saliency termed thematic video saliency}. Video saliency is detected in terms of finding the thematic objects that frequently appear at the salient positions in the video scenes. By representing all image segments in the video as the spatial-temporal context, we build an affinity graph among them, and formulate the thematic object discovery as a novel cohesive...
Biological cues inherent in human motion play an important role in the context of social communication. While recognizing the gender of other people is important for humans, security, advertisement and population statistics systems could also benefit from such kind of information. In this work for first time we propose a method suitable for real time gait based gender recognition relying on poses...
Hand pose estimation from video is essential for a number of applications such as automatic sign language recognition and robot learning from demonstration. However, hand pose estimation is made difficult by the high degree of articulation of the hand; a realistic hand model is described with at least 35 dimensions, which means that it can assume a wide variety of poses, and there is a very high degree...
In this paper, we present a comparative evaluation of several appearance and shape descriptors in the context of 3D human pose estimation. Among the shape descriptors, we evaluate the Discrete Cosine Transform (DCT) and the Histogram of Shape Context (HoSC) descriptors. The five appearance descriptors that we evaluate are all variants of the Histogram of Oriented Gradients (HOG) descriptor. We evaluate...
In the context of music indexation, it would be useful to have a precise information about the number of sources performing; a source is a solo voice or an isolated instrument which produces a single note at any time. This correspondence discusses the automatic distinction between monophonic music excerpts, where only one source is present, and polyphonic ones. Our method is based on the analysis...
The knowledge about the body orientation of humans can improve speed and performance of many service components of a smart-room. Since many of such components run in parallel, an estimator to acquire this knowledge needs a very low computational complexity. In this paper we address these two points with a fast and efficient algorithm using the smart-room's multiple camera output. The estimation is...
In this paper we propose a novel appearance descriptor for 3D human pose estimation from monocular images using a learning-based technique. Our image-descriptor is based on the intermediate local appearance descriptors that we design to encapsulate local appearance context and to be resilient to noise. We encode the image by the histogram of such local appearance context descriptors computed in an...
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