Sensor-Assisted Face Tracking
Generally, face detection and tracking focus only on visual data analysis. In this paper, we propose a novel method for face tracking in camera video. By making use of the context metadata captured by wearable sensors on human bodies at the time of video recording, we could improve the performance a...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-01-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/173535 |
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| _version_ | 1849695977522331648 |
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| author | Dingbo Duan Jian Ma |
| author_facet | Dingbo Duan Jian Ma |
| author_sort | Dingbo Duan |
| collection | DOAJ |
| description | Generally, face detection and tracking focus only on visual data analysis. In this paper, we propose a novel method for face tracking in camera video. By making use of the context metadata captured by wearable sensors on human bodies at the time of video recording, we could improve the performance and efficiency of traditional face tracking algorithms. Specifically, when subjects wearing motion sensors move around in the field of view (FOV) of a camera, motion features collected by those sensors help to locate frames most probably containing faces from the recorded video and thus save large amount of time spent on filtering out faceless frames and cut down the proportion of false alarms. We conduct extensive experiments to evaluate the proposed method and achieve promising results. |
| format | Article |
| id | doaj-art-cd55525e30854b518e59a7fa0df7dac3 |
| institution | DOAJ |
| issn | 1550-1477 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-cd55525e30854b518e59a7fa0df7dac32025-08-20T03:19:35ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-01-011110.1155/2015/173535173535Sensor-Assisted Face TrackingDingbo Duan0Jian Ma1 Beijing University of Posts and Telecommunications, Beijing 100876, China Smart Sensing Stars, Co. Ltd., Wuxi 214000, ChinaGenerally, face detection and tracking focus only on visual data analysis. In this paper, we propose a novel method for face tracking in camera video. By making use of the context metadata captured by wearable sensors on human bodies at the time of video recording, we could improve the performance and efficiency of traditional face tracking algorithms. Specifically, when subjects wearing motion sensors move around in the field of view (FOV) of a camera, motion features collected by those sensors help to locate frames most probably containing faces from the recorded video and thus save large amount of time spent on filtering out faceless frames and cut down the proportion of false alarms. We conduct extensive experiments to evaluate the proposed method and achieve promising results.https://doi.org/10.1155/2015/173535 |
| spellingShingle | Dingbo Duan Jian Ma Sensor-Assisted Face Tracking International Journal of Distributed Sensor Networks |
| title | Sensor-Assisted Face Tracking |
| title_full | Sensor-Assisted Face Tracking |
| title_fullStr | Sensor-Assisted Face Tracking |
| title_full_unstemmed | Sensor-Assisted Face Tracking |
| title_short | Sensor-Assisted Face Tracking |
| title_sort | sensor assisted face tracking |
| url | https://doi.org/10.1155/2015/173535 |
| work_keys_str_mv | AT dingboduan sensorassistedfacetracking AT jianma sensorassistedfacetracking |