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Video Based Pedestrian Height Estimation Using Winer Optimization
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 Title & Authors
Video Based Pedestrian Height Estimation Using Winer Optimization
Jeon, Sang Hee; Song, Jong Kwan; Park, Jang Sik; Yoon, Byung Woo;
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 Abstract
In this paper, we proposed a method which can detect pedestrians from CCTV video and estimate the height of the detected objects. We separate the foreground using Gaussian mixture model and the pedestrian is detected using the conditions such as the width-height ratio and the size of the candidate objects. In order to obtain the optimal model for estimating the height of pedestrian, we get many training data from the pedestrian whose height is known. Using these training data, we designed optimal Wiener height estimator and used to estimate the height of pedestrians. The height of the pedestrian at various distance is estimated and the accuracy is evaluated. In the experimental results, proposed method shows that it can estimate the height of pedestrian for various positions effectively.
 Keywords
Height Estimation;Gaussian Mixture Model;Wiener Estimation;
 Language
Korean
 Cited by
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