標題: REAL-TIME UPPER BODY POSE ESTIMATION FROM DEPTH IMAGES
作者: Tsai, Ming-Han
Chen, Kuan-Hua
Lin, I-Chen
交大名義發表
National Chiao Tung University
關鍵字: Pose estimation;depth image;arm pose;randomized forest
公開日期: 2015
摘要: Estimating upper body poses from a sequence of depth images is a challenging problem. Lately, the state-of-art work adopted a randomized forest method to label human parts in real time. However, it requires enormous training data to obtain favorable results. In this paper, we propose using a novel two-stage method to estimate the probability maps of upper body parts of users. These maps are then used to evaluate the region fitness of body parts for pose recovery. Experiments show that the proposed method can obtain satisfactory outcome in real time and it requires a moderate size of training data.
URI: http://hdl.handle.net/11536/135267
ISBN: 978-1-4799-8339-1
ISSN: 1522-4880
期刊: 2015 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
起始頁: 2234
結束頁: 2238
Appears in Collections:Conferences Paper