生成型学習法を用いた姿勢変化に頑健な歩行者検出の検討

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  • 生成型学習法を用いた姿勢変化に頑健な歩行者検出の検討(一般セッション,医用画像処理分野における計測・認識・理解)
  • セイセイガタ ガクシュウホウ オ モチイタ シセイ ヘンカ ニ ガンケン ナ ホコウシャ ケンシュツ ノ ケントウ
  • A study on a method for stable pedestrian detection against pose changes with generative learning

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Abstract

Recently, pedestrian detection from in-vehicle camera images is being focused. However, it is difficult to detect pedestrians due to the variety of their poses and backgrounds. To tackle this problem, we propose a method to detect various pedestrians from in-vehicle camera images. To deal with changes of pedestrians' pose and environment, most existing methods making use of their appearance require to prepare a lot of pedestrian images manually. The proposed method classifies a small number of pedestrian images into several pose classes and then generates various pedestrian images from each pose class. Finally, the proposed method constructs a classifier based on multiple templates from each pedestrian pose. Experimental results showed that the detection accuracy of the method outperformed existing methods, and we confirmed its effectiveness. [Note]This document is an informal handout distributed at an IEICE TC-PRMU workshop.

IEICE Technical Report;IE2011-31, PRMU2011-23, MI2011-23

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