Bilal, Sara Mohammed Osman Saleh and Akmeliawati, Rini and Shafie, Amir Akramin and Salami, Momoh Jimoh Eyiomika (2013) Human upper body pose region estimation. In: Recent advances in robotics and automation, studies in computational intelligence. Studies in computational intelligence (480). Springer, London, pp. 335-344. ISBN 9783642373862 / 9783642373879
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Abstract
The objective of this chapter is to estimate 2D human pose for action recognition and especially for sign language recognition systems which require not only the hand motion trajectory to be classified but also facial features, Human Upper Body (HUB) and hand position with respect to other HUB parts. We propose an approach that progressively reduces the search space for body parts and can greatly improve chance to estimate the HUB pose. This involves two contributions: (a) a fast and robust search algorithm for HUB parts based on head size has been introduced for real time implementations. (b) Scaling the extracted parts during body orientation was attained using partial estimation of face size. The outcome of the system makes it applicable for real-time applications such as sign languages recognition systems. The method is fully automatic and self-initializing using a Haar-like face region. The tracking the HUB pose is based on the face detection algorithm. Our evaluation was done mainly using 50 images from INRIA Person Dataset.
Item Type: | Book Chapter |
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Additional Information: | 6951/31777 |
Uncontrolled Keywords: | human upper body |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Engineering |
Depositing User: | Prof. Dr. Rini Akmeliawati |
Date Deposited: | 02 Oct 2013 17:04 |
Last Modified: | 09 Mar 2014 03:57 |
URI: | http://irep.iium.edu.my/id/eprint/31777 |
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