Difference between revisions of "Publications:Face Tracking Using Optical Flow : Development of a Real-Time AdaBoost Cascade Face Tracker"
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| − | |Name=Ranftl, Andreas (Högskolan i Halmstad | + | |Name=Ranftl, Andreas (Högskolan i Halmstad (2804), Akademin för informationsteknologi (16904));Alonso-Fernandez, Fernando (feralo) (0000-0002-1400-346X) (Högskolan i Halmstad (2804), Akademin för informationsteknologi (16904), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), CAISR Centrum för tillämpade intelligenta system (IS-lab) (13650));Karlsson, Stefan (stekar) (Högskolan i Halmstad (2804), Akademin för informationsteknologi (16904), Halmstad Embedded and Intelligent Systems Research (EIS) (3938), CAISR Centrum för tillämpade intelligenta system (IS-lab) (13650)) |
|Title=Face Tracking Using Optical Flow : Development of a Real-Time AdaBoost Cascade Face Tracker | |Title=Face Tracking Using Optical Flow : Development of a Real-Time AdaBoost Cascade Face Tracker | ||
|PublicationType=Conference Paper | |PublicationType=Conference Paper | ||
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|CreatedDate=2015-08-06 | |CreatedDate=2015-08-06 | ||
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| − | |LastUpdated=2015- | + | |LastUpdated=2015-09-29 |
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Latest revision as of 22:40, 30 September 2016
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| Title | Face Tracking Using Optical Flow : Development of a Real-Time AdaBoost Cascade Face Tracker |
|---|---|
| Author | |
| Year | 2015 |
| PublicationType | Conference Paper |
| Journal | |
| HostPublication | |
| Conference | 14th International Conference of the Biometrics Special Interest Group, BIOSIG, Darmstadt, Germany, 9-11 September, 2015 |
| DOI | |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:844486 |
| Abstract | In this paper a novel face tracking approach is presented where optical flow information is incorporated into the Viola-Jones face detection algorithm. In the original algorithm from Viola and Jones face detection is static as information from previous frames is not considered. In contrast to the Viola-Jones face detector and also to other known dynamic enhancements, the proposed facetracker preserves information about near-positives. The algorithm builds a likelihood map from the intermediate results of the Viola-Jones algorithm which is extrapolated using optical flow. The objects get extracted from the likelihood map using image segmentation techniques. All steps can be computed very efficiently in real-time. The tracker is verified on the Boston Head Tracking Database showing that the proposed algorithm outperforms the standard Viola-Jones face detector. |
