Human upper body pose region estimation
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 part...
| Main Authors: | , , , |
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| Format: | Book Chapter |
| Language: | English |
| Published: |
Springer
2013
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/31777/1/Book_RINI.pdf |
| _version_ | 1825647446220341248 |
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| author | Bilal, Sara Mohammed Osman Saleh Akmeliawati, Rini Shafie, Amir Akramin Salami, Momoh Jimoh Eyiomika |
| author_facet | Bilal, Sara Mohammed Osman Saleh Akmeliawati, Rini Shafie, Amir Akramin Salami, Momoh Jimoh Eyiomika |
| author_sort | Bilal, Sara Mohammed Osman Saleh |
| collection | IIUM |
| description | 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. |
| first_indexed | 2024-03-05T23:17:44Z |
| format | Book Chapter |
| id | oai:generic.eprints.org:31777 |
| institution | International Islamic University Malaysia |
| language | English |
| last_indexed | 2024-03-05T23:17:44Z |
| publishDate | 2013 |
| publisher | Springer |
| record_format | dspace |
| spelling | oai:generic.eprints.org:317772014-03-08T19:57:54Z http://irep.iium.edu.my/31777/ Human upper body pose region estimation Bilal, Sara Mohammed Osman Saleh Akmeliawati, Rini Shafie, Amir Akramin Salami, Momoh Jimoh Eyiomika TK Electrical engineering. Electronics Nuclear engineering 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. Springer 2013 Book Chapter PeerReviewed application/pdf en http://irep.iium.edu.my/31777/1/Book_RINI.pdf 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 http://www.springer.com/engineering/computational+intelligence+and+complexity/book/978-3-642-37386-2 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Bilal, Sara Mohammed Osman Saleh Akmeliawati, Rini Shafie, Amir Akramin Salami, Momoh Jimoh Eyiomika Human upper body pose region estimation |
| title | Human upper body pose region estimation |
| title_full | Human upper body pose region estimation |
| title_fullStr | Human upper body pose region estimation |
| title_full_unstemmed | Human upper body pose region estimation |
| title_short | Human upper body pose region estimation |
| title_sort | human upper body pose region estimation |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://irep.iium.edu.my/31777/1/Book_RINI.pdf |
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