Protuberance of depth : Detecting interest points from a depth image

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Detecting distinctive interest points in a scene or an object allows estimating which details a human finds interesting in advance to understand the scene or the object. This also forms the important basis of a variety of latter tasks related to visual detection and tracking. In this paper, we propose a simple but effective approach to extract the feature from a depth image, namely Protuberance of Depth (PoD). The proposed approach semantically explores the inherent feature representing three-dimensional protuberance by using depth which only contains two-dimensional distance information. Our approach directly allows detecting consistent interest points in a depth image. The experimental results show that our method is effective against the isometric deformation and rotation of a depth region and is applicable for real-time applications.

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论文评审过程:Received 26 March 2019, Revised 29 January 2020, Accepted 3 February 2020, Available online 6 February 2020, Version of Record 18 February 2020.

论文官网地址:https://doi.org/10.1016/j.cviu.2020.102927