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Author (up) Iiris Lusi; Sergio Escalera; Gholamreza Anbarjafari edit  doi
openurl 
  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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