Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter
A new method is presented for integration of audio and visual information in multiple target tracking applications. The proposed approach uses a Bayesian filtering formulation and exploits multi-Bernoulli random finite set approximations. The work presented in this paper is the first principled Baye...
| Main Authors: | , , , |
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| Format: | Conference Paper |
| Published: |
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/55473 |
| _version_ | 1848759630919892992 |
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| author | Hoseinnezhad, R. Vo, Ba-Ngu Vo, Ba Tuong Suter, D. |
| author_facet | Hoseinnezhad, R. Vo, Ba-Ngu Vo, Ba Tuong Suter, D. |
| author_sort | Hoseinnezhad, R. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | A new method is presented for integration of audio and visual information in multiple target tracking applications. The proposed approach uses a Bayesian filtering formulation and exploits multi-Bernoulli random finite set approximations. The work presented in this paper is the first principled Bayesian estimation approach to solve the sensor fusion problems that involve intermittent sensory data (e.g. audio data for a person who occasionally speaks.) We have examined our method with case studies from the SPEVI database. The results show nearly perfect tracking of people not only when they are silent but also when they are not visible to the camera (but speaking). © 2011 IEEE. |
| first_indexed | 2025-11-14T10:02:57Z |
| format | Conference Paper |
| id | curtin-20.500.11937-55473 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:02:57Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-554732018-03-29T09:09:26Z Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter Hoseinnezhad, R. Vo, Ba-Ngu Vo, Ba Tuong Suter, D. A new method is presented for integration of audio and visual information in multiple target tracking applications. The proposed approach uses a Bayesian filtering formulation and exploits multi-Bernoulli random finite set approximations. The work presented in this paper is the first principled Bayesian estimation approach to solve the sensor fusion problems that involve intermittent sensory data (e.g. audio data for a person who occasionally speaks.) We have examined our method with case studies from the SPEVI database. The results show nearly perfect tracking of people not only when they are silent but also when they are not visible to the camera (but speaking). © 2011 IEEE. 2011 Conference Paper http://hdl.handle.net/20.500.11937/55473 10.1109/ICASSP.2011.5946942 restricted |
| spellingShingle | Hoseinnezhad, R. Vo, Ba-Ngu Vo, Ba Tuong Suter, D. Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter |
| title | Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter |
| title_full | Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter |
| title_fullStr | Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter |
| title_full_unstemmed | Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter |
| title_short | Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter |
| title_sort | bayesian integration of audio and visual information for multi-target tracking using a cb-member filter |
| url | http://hdl.handle.net/20.500.11937/55473 |