Point Anywhere: Directed Object Estimation from Omnidirectional Images

• URL: http://arxiv.org/abs/2308.01010v1
• Date: Wed, 2 Aug 2023 08:32:43 GMT
• Title: Point Anywhere: Directed Object Estimation from Omnidirectional Images
• Authors: Nanami Kotani and Asako Kanezaki
• Abstract summary: We propose a method using an omnidirectional camera to eliminate the user/object position constraint and the left/right constraint of the pointing arm. The proposed method enables highly accurate estimation by repeatedly extracting regions of interest from the equirectangular image.
• Score: 10.152838128195468
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: One of the intuitive instruction methods in robot navigation is a pointing gesture. In this study, we propose a method using an omnidirectional camera to eliminate the user/object position constraint and the left/right constraint of the pointing arm. Although the accuracy of skeleton and object detection is low due to the high distortion of equirectangular images, the proposed method enables highly accurate estimation by repeatedly extracting regions of interest from the equirectangular image and projecting them onto perspective images. Furthermore, we found that training the likelihood of the target object in machine learning further improves the estimation accuracy.

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