HOPC: Histogram of Oriented Principal Components of 3D Pointclouds for Action Recognition

Autor:	Rahmani, Hossein, Mahmood, Arif, Huynh, Du Q., Mian, Ajmal
Rok vydání:	2014
Předmět:	Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	Existing techniques for 3D action recognition are sensitive to viewpoint variations because they extract features from depth images which change significantly with viewpoint. In contrast, we directly process the pointclouds and propose a new technique for action recognition which is more robust to noise, action speed and viewpoint variations. Our technique consists of a novel descriptor and keypoint detection algorithm. The proposed descriptor is extracted at a point by encoding the Histogram of Oriented Principal Components (HOPC) within an adaptive spatio-temporal support volume around that point. Based on this descriptor, we present a novel method to detect Spatio-Temporal Key-Points (STKPs) in 3D pointcloud sequences. Experimental results show that the proposed descriptor and STKP detector outperform state-of-the-art algorithms on three benchmark human activity datasets. We also introduce a new multiview public dataset and show the robustness of our proposed method to viewpoint variations. Comment: ECCV 2014
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1408.3809 Zobrazit plný text záznamu View this record from Arxiv