Recognizing Faces of Moving People by Hierarchical Image-Set Matching

[Abstract]

This paper proposes a novel method for recognizing faces in a cluster of moving people. In this task, there are two problems caused by motion, which are occlusions, and changes in facial pose and illumination. Multiple cameras are used to acquire near-frontal faces to avoid occlusions and profile faces. The Hierarchical Image-Set Matching (HISM) creates a distribution for each individual by integrating a set of face images of the same individual acquired from the multiple cameras. By adopting a method for comparing between test and training distributions in identification, variation in pose and illumination is alleviated, and good recognition accuracy can be obtained. Experimental results using video sequences containing 349 people show that the proposed method achieves high recognition performance compared with conventional methods, which use frame-by-frame identification and a distribution obtained from a single camera.

[Publication]

• Masashi Nishiyama, Mayumi Yuasa, Tomoyuki Shibata, Tomokazu Wakasugi, Tomokazu Kawahara, and Osamu Yamaguchi,
  Recognizing Faces of Moving People by Hierarchical Image-Set Matching,
  Proceedings of IEEE Computer Society Workshop on Biometrics, pp. 1 - 8, June 2007. [Best Paper Award]

[Publications (Japanese) ]

• 西山 正志, 湯浅 真由美, 柴田 智行, 若杉 智和, 山口 修,
  顔画像の階層的な対応付けを用いた複数歩行者の認識,
  電子情報通信学会論文誌 D, Vol. J90-D, No. 8, pp. 2191 - 2201, 2007.
• 西山 正志, 湯浅 真由美, 若杉 智和, 柴田 智行, 山口 修,
  断片的な動画像の対応付けを利用した歩行者認識,
  第12回 画像センシングシンポジウム (SSII), pp. 231 - 238, June 2006. [優秀論文賞]