Simultaneous object segmentation and recognition by merging CNN outputs from uniformly distributed multiple viewpoints

Yoshikatsu Nakajima, Hideo Saito

研究成果: Article

抜粋

We propose a novel object recognition system that is able to (i) work in real-time while reconstructing segmented 3D maps and simultaneously recognize objects in a scene, (ii) manage various kinds of objects, including those with smooth surfaces and those with a large number of categories, utilizing a CNN for feature extraction, and (iii) maintain high accuracy no matter how the camera moves by distributing the viewpoints for each object uniformly and aggregating recognition results from each distributed viewpoint as the same weight. Through experiments, the advantages of our system with respect to current state-of-the-art object recognition approaches are demonstrated on the UW RGB-D Dataset and Scenes and on our own scenes prepared to verify the effectiveness of the Viewpoint-Class-based approach.

元の言語English
ページ(範囲)1308-1316
ページ数9
ジャーナルIEICE Transactions on Information and Systems
E101D
発行部数5
DOI
出版物ステータスPublished - 2018 5 1

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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