Activity recognition using visual tracking and RFID
Computer vision-based articulated human motion tracking is attractive for many applications since it allows unobtrusive and passive estimation of people's activities. Although much progress has been made on human-only tracking, the visual tracking of people that interact with objects such as to...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2007
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| _version_ | 1797052515806609408 |
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| author | Krahnstoever, N Rittscher, J Tu, P Chean, K Tomlinson, T |
| author_facet | Krahnstoever, N Rittscher, J Tu, P Chean, K Tomlinson, T |
| author_sort | Krahnstoever, N |
| collection | OXFORD |
| description | Computer vision-based articulated human motion tracking is attractive for many applications since it allows unobtrusive and passive estimation of people's activities. Although much progress has been made on human-only tracking, the visual tracking of people that interact with objects such as tools, products, packages, and devices is considerably more challenging. The wide variety of objects, their varying visual appearance, and their varying (and often small) size makes a vision-based understanding of person-object interactions very difficult. To alleviate this problem for at least some application domains, we propose a framework that combines visual human motion tracking with RFID based object tracking. We customized commonly available RFID technology to obtain orientation estimates of objects in the field of RFID emitter coils. The resulting fusion of visual human motion tracking and RFID-based object tracking enables the accurate estimation of high-level interactions between people and objects for application domains such as retail, home-care, workplace-safety, manufacturing and others. |
| first_indexed | 2024-03-06T18:32:40Z |
| format | Journal article |
| id | oxford-uuid:0a320be1-b10e-426e-94e1-32c67c6a532b |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T18:32:40Z |
| publishDate | 2007 |
| record_format | dspace |
| spelling | oxford-uuid:0a320be1-b10e-426e-94e1-32c67c6a532b2022-03-26T09:22:28ZActivity recognition using visual tracking and RFIDJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:0a320be1-b10e-426e-94e1-32c67c6a532bEnglishSymplectic Elements at Oxford2007Krahnstoever, NRittscher, JTu, PChean, KTomlinson, TComputer vision-based articulated human motion tracking is attractive for many applications since it allows unobtrusive and passive estimation of people's activities. Although much progress has been made on human-only tracking, the visual tracking of people that interact with objects such as tools, products, packages, and devices is considerably more challenging. The wide variety of objects, their varying visual appearance, and their varying (and often small) size makes a vision-based understanding of person-object interactions very difficult. To alleviate this problem for at least some application domains, we propose a framework that combines visual human motion tracking with RFID based object tracking. We customized commonly available RFID technology to obtain orientation estimates of objects in the field of RFID emitter coils. The resulting fusion of visual human motion tracking and RFID-based object tracking enables the accurate estimation of high-level interactions between people and objects for application domains such as retail, home-care, workplace-safety, manufacturing and others. |
| spellingShingle | Krahnstoever, N Rittscher, J Tu, P Chean, K Tomlinson, T Activity recognition using visual tracking and RFID |
| title | Activity recognition using visual tracking and RFID |
| title_full | Activity recognition using visual tracking and RFID |
| title_fullStr | Activity recognition using visual tracking and RFID |
| title_full_unstemmed | Activity recognition using visual tracking and RFID |
| title_short | Activity recognition using visual tracking and RFID |
| title_sort | activity recognition using visual tracking and rfid |
| work_keys_str_mv | AT krahnstoevern activityrecognitionusingvisualtrackingandrfid AT rittscherj activityrecognitionusingvisualtrackingandrfid AT tup activityrecognitionusingvisualtrackingandrfid AT cheank activityrecognitionusingvisualtrackingandrfid AT tomlinsont activityrecognitionusingvisualtrackingandrfid |