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Proceedings Paper

Sensor specific distributions for improved tracking of people
Author(s): Rik Bellens; Sidharta Gautama; Johannes P.F. D'Haeyer
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Paper Abstract

In this paper, we examine sensor specific distributions of local image operators (edge and line detectors), which describe the appearance of people in video sequences. The distributions are used to describe a probabilistic articulated motion model to track the gestures of a person in terms of arms and body movement. The distributions are based on work of Sidenbladh where general distributions are examined, collected over images found on the internet. In our work, we focus on the statistics of one sensor, in our case a standard webcam, and examine the influence of image noise and scale. We show that although the general shape of the distributions published by Sidenbladh are found, important anomalies occur which are due to image noise and reduced resolution. Taking into account the effects of noise and blurring on the scale space response of edge and line detectors improves the overall performance of the model. The original distributions introduced a bias towards small sharp boundaries over large blurred boundaries. In the case of arms and legs which often appear blurred in the image, this bias is unwanted. Incorporating our modifications in the distributions removes the bias and makes the tracking more robust.

Paper Details

Date Published: 14 March 2005
PDF: 11 pages
Proc. SPIE 5685, Image and Video Communications and Processing 2005, (14 March 2005); doi: 10.1117/12.585273
Show Author Affiliations
Rik Bellens, Univ. of Ghent (Belgium)
Sidharta Gautama, Univ. of Ghent (Belgium)
Johannes P.F. D'Haeyer, Univ. of Ghent (Belgium)


Published in SPIE Proceedings Vol. 5685:
Image and Video Communications and Processing 2005
Amir Said; John G. Apostolopoulos, Editor(s)

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