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Author (up) Iiris Lusi; Sergio Escalera; Gholamreza Anbarjafari
Title Human Head Pose Estimation on SASE database using Random Hough Regression Forests Type Conference Article
Year 2016 Publication 23rd International Conference on Pattern Recognition Workshops Abbreviated Journal
Volume 10165 Issue Pages
Keywords
Abstract In recent years head pose estimation has become an important task in face analysis scenarios. Given the availability of high resolution 3D sensors, the design of a high resolution head pose database would be beneficial for the community. In this paper, Random Hough Forests are used to estimate 3D head pose and location on a new 3D head database, SASE, which represents the baseline performance on the new data for an upcoming international head pose estimation competition. The data in SASE is acquired with a Microsoft Kinect 2 camera, including the RGB and depth information of 50 subjects with a large sample of head poses, allowing us to test methods for real-life scenarios. We briefly review the database while showing baseline head pose estimation results based on Random Hough Forests.
Address Cancun; Mexico; December 2016
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference ICPRW
Notes HuPBA; Approved no
Call Number Admin @ si @ LEA2016b Serial 2910
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