Body Height Estimation System Based on Binocular Vision

Guangyi Yang, Deshi Li, Guobao Ru, Jiahua Cao, Weizheng Jin


In this paper, we propose a novel approach to estimate body height from video sequences based on binocular stereo vision. Firstly, we built a parallel binocular stereo vision device and detected the foreground by using Gaussian mixture model. After shadow elimination, we proposed the contour screening algorithm to obtain the human foreground and the top point in the foreground image. Then, we detected SURF feature points in the binocular images and screened them for 3 times to calculate the disparity of the head. After that, the height of human bodies can be estimated with the calibration parameters of binocular cameras. The experimental results demonstrate that the proposed method has higher measurement accuracy and spends less time which proves the effectiveness of the method.


binocular vision; height measurement; human body; Gaussian mixture model; feature matching

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International Journal of Online and Biomedical Engineering (iJOE) – eISSN: 2626-8493
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