Graph Representation of Images in Scale-Space with Application to Face Detection

• MARUTA Hidetoshi

  Information Science Center, Nagasaki University

• KOZAKAYA Tatsuo

  Toshiba Corporation

• KOIKE Yasuharu

  Precision and Intelligen Laboratory, Tokyo Institute of Technology

• SATO Mokoto

  Precision and Intelligen Laboratory, Tokyo Institute of Technology

抄録

In the image recognition problem, it is very important how we represent the image. Considering this, we propose a new representational method of images based on the stability in scale-space. In our method, the image is segmented and represented as a hierarchical region graph in scale-space. The object is represented as feature graph, which is subgraph of region graph. In detail, the region graph is denned on the image with the relation of each segment hierarchically. And the feature graph is determined based on the "life-time" of the graph of the object in scale-space. This "life-time" means how long feature graph lives when the scale parameter is increased. We apply our method to the face detection problem, which is foundmental and difficult problem in face recognition. We determine the feature graph of the frontal human face statistical point of view. We also build the face detection system using this feature graph to show how our method works efficiently.

収録刊行物

• IEICE transactions on information and systems

  IEICE transactions on information and systems 86 (7), 1221-1227, 2003-07-01

  一般社団法人電子情報通信学会

キーワード

• scale-space analysis
• graph representation
• face detection

詳細情報

• CRID: 1571980077394262400
• NII論文ID: 110003213784
• NII書誌ID: AA10826272
• ISSN: 09168532
• 本文言語コード: en
• データソース種別:
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