Person recognition by stereo model-based matching

Daisuke Itou; Jianing Zhu; Yasushi Mae; Mamoru Minami

doi:10.1109/SICE.2006.314812

Person recognition by stereo model-based matching

Daisuke Itou, Jianing Zhu, Yasushi Mae, Mamoru Minami

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

This paper describes a method for detecting persons and measuring the 3D position in real time by stereo camera. We employ an unprocessed input color image termed here as raw-image to execute recognition process by model-based matching method. A person on the image is detected by Model-based matching and Genetic Algorithm. Face is defined as a circular skin color model for times of the image is evaluated by the face model. The maximum of evaluation value is searched by Genetic Algorithm. The position with the maximum evaluation value is detected as target person's face. The distance from the camera to the person is calculated by the disparity of detected person on the stereo images. The method obtains the person's position and height. Experimental results show the effectiveness of our proposed system.

Original language	English
Title of host publication	2006 SICE-ICASE International Joint Conference
Pages	2822-2827
Number of pages	6
DOIs	https://doi.org/10.1109/SICE.2006.314812
Publication status	Published - Dec 1 2006
Externally published	Yes
Event	2006 SICE-ICASE International Joint Conference - Busan, Korea, Republic of Duration: Oct 18 2006 → Oct 21 2006

Publication series

Name	2006 SICE-ICASE International Joint Conference

Other

Other	2006 SICE-ICASE International Joint Conference
Country	Korea, Republic of
City	Busan
Period	10/18/06 → 10/21/06

Keywords

Person recognition
Real-time recognition
Stereo model-based matching

ASJC Scopus subject areas

Computer Science Applications
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/SICE.2006.314812

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Cite this

Itou, D., Zhu, J., Mae, Y., & Minami, M. (2006). Person recognition by stereo model-based matching. In 2006 SICE-ICASE International Joint Conference (pp. 2822-2827). [4108127] (2006 SICE-ICASE International Joint Conference). https://doi.org/10.1109/SICE.2006.314812

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title = "Person recognition by stereo model-based matching",

abstract = "This paper describes a method for detecting persons and measuring the 3D position in real time by stereo camera. We employ an unprocessed input color image termed here as raw-image to execute recognition process by model-based matching method. A person on the image is detected by Model-based matching and Genetic Algorithm. Face is defined as a circular skin color model for times of the image is evaluated by the face model. The maximum of evaluation value is searched by Genetic Algorithm. The position with the maximum evaluation value is detected as target person's face. The distance from the camera to the person is calculated by the disparity of detected person on the stereo images. The method obtains the person's position and height. Experimental results show the effectiveness of our proposed system.",

keywords = "Person recognition, Real-time recognition, Stereo model-based matching",

author = "Daisuke Itou and Jianing Zhu and Yasushi Mae and Mamoru Minami",

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AB - This paper describes a method for detecting persons and measuring the 3D position in real time by stereo camera. We employ an unprocessed input color image termed here as raw-image to execute recognition process by model-based matching method. A person on the image is detected by Model-based matching and Genetic Algorithm. Face is defined as a circular skin color model for times of the image is evaluated by the face model. The maximum of evaluation value is searched by Genetic Algorithm. The position with the maximum evaluation value is detected as target person's face. The distance from the camera to the person is calculated by the disparity of detected person on the stereo images. The method obtains the person's position and height. Experimental results show the effectiveness of our proposed system.

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