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Two dimensional shape models have been successfully applied to solve many problems in computer vision such as object tracking, recognition and segmentation. Typically, 2D shape models (e.g. Point Distribution Models, Active Shape Models) are learned from a discrete set of image landmarks once the rigid transformations are removed applying Procrustes Analysis (PA). However, the standard PA process...
In this paper, we propose a novel Adaboost template to recognize human upper body poses from disparity images for natural human robot interaction (HRI). First, the upper body poses of standing persons are classified into seven categories of views. For each category, a mean template, variance template, and percentage template are generated. Then, the template region is divided into positive and negative...
In this paper we introduce a large body of virtual human action silhouette (ViHASi) data that we have recently generated for the purpose of evaluating a family of action recognition methods. These are the silhouette-based human action recognition methods. This synthetic multi-camera video data-set consists of 20 action classes, 9 actors and up to 40 synchronized perspective cameras. This data-set...
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