A Person Identification Method Using a Top-View Head Image from an Overhead Camera
Author(s) -
Ryota Nakatani,
Daichi Kouno,
Kazutaka Shimada,
Tsutomu Endo
Publication year - 2012
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2012.p0696
Subject(s) - computer science , artificial intelligence , computer vision , overhead (engineering) , identification (biology) , background subtraction , image (mathematics) , task (project management) , focus (optics) , adaboost , face (sociological concept) , pixel , botany , biology , operating system , social science , physics , management , sociology , classifier (uml) , optics , economics
In this paper, we describe a novel imagebased person identification task. Traditional facebased person identification methods have a low tolerance for occluded situation, such as overlapping of people in an image. We focus on an image from an overhead camera. Using the overhead camera reduces a restriction of the installation location of a camera and solves the problem of occluded images. First, our method identifies the person’s area in a captured image by using background subtraction. Then, it extracts four features from the area; (1) body size, (2) hair color, (3) hairstyle and (4) hair whorl. We apply the four features into the AdaBoost algorithm. Experimental result shows the effectiveness of our method.
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