Static human body postures recognition in video sequences using the belief theory

Static human body postures recognition in video sequences using the belief theory

This paper presents a system that can automatically recognize four different static human body postures in video sequences. The considered postures are standing, sitting, squatting, and lying. The recognition is based on data fusion using the belief theory. The data come from the persons 2D segmenta...

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Hauptverfasser: Girondel, V., Bonnaud, L., Caplier, A., Rombaut, M.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Arm
Biological system modeling
Color
Distance measurement
Face detection
Human computer interaction
Image recognition
Skin
Speech analysis
Video sequences
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creator Girondel, V.
Bonnaud, L.
Caplier, A.
Rombaut, M.
description This paper presents a system that can automatically recognize four different static human body postures in video sequences. The considered postures are standing, sitting, squatting, and lying. The recognition is based on data fusion using the belief theory. The data come from the persons 2D segmentation and from their face localization. It consists in distance measurements relative to a reference posture ("Da Vinci posture": standing, arms stretched horizontally). The segmentation is based on an adaptive background removal algorithm. The face localization process uses skin detection based on color information with an adaptive thresholding. The efficiency and the limits of the recognition system are highlighted thanks to the analysis of a great number of results. This system allows real-time processing.
doi_str_mv 10.1109/ICIP.2005.1529987
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subjects Arm
Biological system modeling
Color
Distance measurement
Face detection
Human computer interaction
Image recognition
Skin
Speech analysis
Video sequences
title Static human body postures recognition in video sequences using the belief theory
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