Partial least squares-based human upper body orientation estimation with combined detection and tracking
作者：
Highlights：
• We propose a method for estimating the human upper body orientation.
• Our algorithm uses partial least squares-based gradient and texture feature models.
• Integration with an UKF-based movement prediction increases the performance.
• Comparison with the state-of-the-art shows the benefit of our algorithm.
• Experiment results using image, video, and camera are provided.
摘要
•We propose a method for estimating the human upper body orientation.•Our algorithm uses partial least squares-based gradient and texture feature models.•Integration with an UKF-based movement prediction increases the performance.•Comparison with the state-of-the-art shows the benefit of our algorithm.•Experiment results using image, video, and camera are provided.
论文关键词：Human upper body orientation,Partial least squares,Multi-level HOG-LBP,Random Forest classifier,UKF tracker
论文评审过程：Received 30 October 2013, Revised 8 March 2014, Accepted 4 August 2014, Available online 11 August 2014.
论文官网地址：https://doi.org/10.1016/j.imavis.2014.08.002
