The Development of Color CHLAC Features for Object Exploration in 3D Map

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  • Harada Tatsuya
    Graduate School of Information Science and Technology, the University of Tokyo
  • Kanezaki Asako
    Graduate School of Information Science and Technology, the University of Tokyo
  • Kuniyoshi Yasuo
    Graduate School of Information Science and Technology, the University of Tokyo

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  • 三次元環境地図からの物体探索タスク応用を目指したカラー立体高次局所自己相関特徴の開発
  • 3ジゲン カンキョウ チズ カラ ノ ブッタイ タンサク タスク オウヨウ オ メザシタ カラー リッタイ コウジ キョクショ ジコ ソウカン トクチョウ ノ カイハツ

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Abstract

We present a new feature “Color Cubic Higher-order Auto-Correlation (Color CHLAC) features” to recognize objects in the real world versatilely and robustly. The new features satisfy the necessary functions for the exploration of objects in a three-dimensional map. In order to search and retrieve objects in a three-dimensional map, the features should have the co-occurrence of textures and shapes, robustness for partial observations and noise, ability to adapt a widespread environment, scalability, and invariance for many transformations. We studied experiments both in a simulation and a real environment for recognition of objects, which have many kinds of shapes and textures, and then we showed that our proposed features obtain high recognition accuracy in both situations.

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