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In this paper, we consider the problem of tracking human motion with a 22-DOF kinematic model from depth images. In contrast to existing approaches, our system naturally scales to multiple sensors. The motivation behind our approach, termed Multiple Depth Camera Approach (MDCA), is that by using several cameras, we can significantly improve the tracking quality and reduce ambiguities as for example...
Crowd analytics is becoming a highly desirable feature of Intelligent Video Surveillance (IVS) applications. In this paper we propose a new, practical approach that adds very little computational and configuration overhead to an IVS system. The approach extends a standard IVS system, using available video content analysis data and camera calibration information to provide accurate human count estimation...
In this paper, the problem of human detection in crowded scenes is formulated as a maximum a posteriori problem, in which, given a set of candidates, predefined 3-D human shape models are matched with image evidence, provided by foreground extraction and probability of boundary, to estimate the human configuration. The optimal solution is obtained by decomposing the mutually related candidates into...
This paper presents development of an evaluation system for easiness of manipulation of product shapes to design better product shapes. In developing the evaluation system, we concentrate mainly on manipulation which involves handling state such that even when the product is rotating it remains near the hand. The evaluation system consists of a glove type hand posture measuring instrument and physics...
In this paper an algorithmic framework for posture analysis using a single view 3D TOF camera is presented. The 3D human posture parameters are recovered automatically from range data without the usage of body markers. A topological approach is investigated in order to define descriptors suitable to estimate location of body parts and orientation of body articulations. Two Morse function are exploited,...
The ability of a perception system to discern what is important in a scene and what is not is an invaluable asset, with multiple applications in object recognition, people detection and SLAM, among others. In this paper, we aim to analyze all sensory data available to separate a scene into a few physically meaningful parts, which we term structure, while discarding background clutter. In particular,...
Even if the problem of human action categorization from videos has received a lot of attention during the past decade, it remains a challenging problem in operative conditions due to camera motion, occlusion, moving background, illumination changes and the variations of human appearance and postures. In this paper a new motion descriptor, based on a sparse optical flow computed by interest point tracking...
This paper proposes a novel 3-D modeling technique of an object. The existent 3-D modeling techniques such as stereo vision or the factorization recover 3-D shapes of part of an object observed commonly from multiple orientations. This inevitably needs registration among recovered partial shapes in order to obtain an entire 3-D model of the object. The proposed technique recovers entire shape of an...
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