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Research of the new Computer Vision and Mulitmodal Computing at MPI Sarrbruecken
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This talk overviews our recent work both in computer vision and multimodal computing. Object class recognition is one of the most fundamental problems in computer vision and I will discuss several approaches we have been developing. One of these approaches is based on a shape-based model for object class detection that enables explicit knowledge transfer between object classes. Another important problem in computer vision is people detection and tracking. In our work we have aimed to integrate detection and tracking into a common framework that has been recently extended to articulated pose estimation. In the second part of the talk I highlight three approaches to enable activity and gesture recognition in realistic scenarios using wearable sensors: the first address the unsupervised discovery of daily routines; the second introduces a novel body-model based human activity recognition approach; and the third discusses an approach for mobile gesture recognition.
This talk is part of the Microsoft Research Cambridge, public talks series.
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