IEICE Transactions on Information and Systems
Online ISSN : 1745-1361
Print ISSN : 0916-8532
Special Section on Machine Vision and its Applications
Simultaneous Object Segmentation and Recognition by Merging CNN Outputs from Uniformly Distributed Multiple Viewpoints
Yoshikatsu NAKAJIMAHideo SAITO
ジャーナル フリー

2018 年 E101.D 巻 5 号 p. 1308-1316


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.

© 2018 The Institute of Electronics, Information and Communication Engineers
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