Estimating Body Related Soft Biometric Traits in Video Frames. (8th July 2014)
- Record Type:
- Journal Article
- Title:
- Estimating Body Related Soft Biometric Traits in Video Frames. (8th July 2014)
- Main Title:
- Estimating Body Related Soft Biometric Traits in Video Frames
- Authors:
- Arigbabu, Olasimbo Ayodeji
Ahmad, Sharifah Mumtazah Syed
Adnan, Wan Azizun Wan
Yussof, Salman
Iranmanesh, Vahab
Malallah, Fahad Layth - Other Names:
- Yuan Yu-Bo Academic Editor.
- Abstract:
- Abstract : Soft biometrics can be used as a prescreening filter, either by using single trait or by combining several traits to aid the performance of recognition systems in an unobtrusive way. In many practical visual surveillance scenarios, facial information becomes difficult to be effectively constructed due to several varying challenges. However, from distance the visual appearance of an object can be efficiently inferred, thereby providing the possibility of estimating body related information. This paper presents an approach for estimating body related soft biometrics; specifically we propose a new approach based on body measurement and artificial neural network for predicting body weight of subjects and incorporate the existing technique on single view metrology for height estimation in videos with low frame rate. Our evaluation on 1120 frame sets of 80 subjects from a newly compiled dataset shows that the mentioned soft biometric information of human subjects can be adequately predicted from set of frames.
- Is Part Of:
- TheScientificWorldjournal. Volume 2014(2014)
- Journal:
- TheScientificWorldjournal
- Issue:
- Volume 2014(2014)
- Issue Display:
- Volume 2014, Issue 2014 (2014)
- Year:
- 2014
- Volume:
- 2014
- Issue:
- 2014
- Issue Sort Value:
- 2014-2014-2014-0000
- Page Start:
- Page End:
- Publication Date:
- 2014-07-08
- Subjects:
- Science -- Periodicals
Technology -- Periodicals
Medicine -- Periodicals
505 - Journal URLs:
- https://www.hindawi.com/journals/tswj/biblio/ ↗
- DOI:
- 10.1155/2014/460973 ↗
- Languages:
- English
- ISSNs:
- 2356-6140
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 22936.xml