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Human Detection in Overhead View and Near-Field View Scene
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  • Human Detection in Overhead View and Near-Field View Scene
  • Human Detection in Overhead View and Near-Field View Scene
저자명
Jung. Sung-Hoon,Jung. Byung-Hee,Kim. Min-Hwan
간행물명
멀티미디어학회논문지
권/호정보
2008년|11권 6호|pp.860-868 (9 pages)
발행정보
한국멀티미디어학회
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정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

Human detection techniques in outdoor scenes have been studied for a long time to watch suspicious movements or to keep someone from danger. However there are few methods of human detection in overhead or near-field view scenes, while lots of human detection methods in far-field view scenes have been developed. In this paper, a set of five features useful for human detection in overhead view scenes and another set of four useful features in near-field view scenes are suggested. Eight feature-candidates are first extracted by analyzing geometrically varying characteristics of moving objects in samples of video sequences. Then highly contributed features for each view scene to classifying human from other moving objects are selected among them by using a neural network learning technique. Through experiments with hundreds of moving objects, we found that each set of features is very useful for human detection and classification accuracy for overhead view and near-field view scenes was over 90%. The suggested sets of features can be used effectively in a PTZ camera based surveillance system where both the overhead and near-field view scenes appear.