Estimating Body Related Soft Biometric Traits in Video Frames
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 d...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/460973 |
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| author | Olasimbo Ayodeji Arigbabu Sharifah Mumtazah Syed Ahmad Wan Azizun Wan Adnan Salman Yussof Vahab Iranmanesh Fahad Layth Malallah |
| author_facet | Olasimbo Ayodeji Arigbabu Sharifah Mumtazah Syed Ahmad Wan Azizun Wan Adnan Salman Yussof Vahab Iranmanesh Fahad Layth Malallah |
| author_sort | Olasimbo Ayodeji Arigbabu |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-219fc3304e03402993d8bc45a20994c9 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-219fc3304e03402993d8bc45a20994c92025-02-03T01:20:40ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/460973460973Estimating Body Related Soft Biometric Traits in Video FramesOlasimbo Ayodeji Arigbabu0Sharifah Mumtazah Syed Ahmad1Wan Azizun Wan Adnan2Salman Yussof3Vahab Iranmanesh4Fahad Layth Malallah5Department of Computer and Communication Systems Engineering, Universiti Putra Malaysia (UPM), 43400 Serdang, Selangor, MalaysiaDepartment of Computer and Communication Systems Engineering, Universiti Putra Malaysia (UPM), 43400 Serdang, Selangor, MalaysiaDepartment of Computer and Communication Systems Engineering, Universiti Putra Malaysia (UPM), 43400 Serdang, Selangor, MalaysiaDepartment of Systems and Networking, Universiti Tenaga Nasional, Jalan IKRAM-Uniten, 43000 Kajang, MalaysiaDepartment of Computer and Communication Systems Engineering, Universiti Putra Malaysia (UPM), 43400 Serdang, Selangor, MalaysiaDepartment of Computer and Communication Systems Engineering, Universiti Putra Malaysia (UPM), 43400 Serdang, Selangor, MalaysiaSoft 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.http://dx.doi.org/10.1155/2014/460973 |
| spellingShingle | Olasimbo Ayodeji Arigbabu Sharifah Mumtazah Syed Ahmad Wan Azizun Wan Adnan Salman Yussof Vahab Iranmanesh Fahad Layth Malallah Estimating Body Related Soft Biometric Traits in Video Frames The Scientific World Journal |
| title | Estimating Body Related Soft Biometric Traits in Video Frames |
| title_full | Estimating Body Related Soft Biometric Traits in Video Frames |
| title_fullStr | Estimating Body Related Soft Biometric Traits in Video Frames |
| title_full_unstemmed | Estimating Body Related Soft Biometric Traits in Video Frames |
| title_short | Estimating Body Related Soft Biometric Traits in Video Frames |
| title_sort | estimating body related soft biometric traits in video frames |
| url | http://dx.doi.org/10.1155/2014/460973 |
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