距離情報を考慮したパーツ統合による人物検出の高精度化

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タイトル別名
  • Improved Part-based Human Detection Using Depth Information
  • キョリ ジョウホウ オ コウリョ シタ パーツ トウゴウ ニ ヨル ジンブツ ケンシュツ ノ コウセイドカ

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In this paper, we propose a part-based human detection method in which the faces and upper parts of human bodies are first detected separately and then merged. In a crowded scene, it is very difficult to merge the detected faces and upper body parts accurately. We solve the problem by using the depth information obtained from the images. We use a TOF (Time of Flight) camera to capture amplitude and depth images. The detector detects the faces and upper body parts from the amplitude images and merges the parts by using a modified Mean Shift clustering algorithm with depth information. Experimental results show that the proposed method shows good performance in the case of crowded scenes. The proposed method is also better than the human detection method in which depth images are used.

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