Difference between revisions of "Publications:Evaluation Protocol for the DXM2VTS Database and Performance Comparison of Face Detection and Face Tracking on Video"
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| − | |Name=Teferi, Dereje | + | |Name=Teferi, Dereje (dete) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938));Bigun, Josef (josef) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938)) |
|Title=Evaluation Protocol for the DXM2VTS Database and Performance Comparison of Face Detection and Face Tracking on Video | |Title=Evaluation Protocol for the DXM2VTS Database and Performance Comparison of Face Detection and Face Tracking on Video | ||
|PublicationType=Book Chapter | |PublicationType=Book Chapter | ||
Latest revision as of 21:39, 30 September 2016
| Title | Evaluation Protocol for the DXM2VTS Database and Performance Comparison of Face Detection and Face Tracking on Video |
|---|---|
| Author | Dereje Teferi and Josef Bigun |
| Year | 2009 |
| PublicationType | Book Chapter |
| Journal | |
| HostPublication | Proceedings SSBA '09 : Symposium on Image Analysis, Halmstad University, Halmstad, March 18-20, 2009 |
| Conference | |
| DOI | |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:728430 |
| Abstract | Video databases and their corresponding evaluation protocols are used to compare classifiers, such as face detection an tracking. In this paper, a six level evaluation protocol for the Damascened XM2VTS (DXM2VTS) database is presented to measure face detection and tracking performance. Additionally, a novel database containing thousands of videos is created by combining video from the XM2VTS database with a set of newly recorded standardized real-life video used as background and with several realistic degradations, such as motion blur, noise, etc. Moreover, two publicly available and published face detection algorithms, are tested on the six suggested difficulty levels of the protocol. Their performance on video in terms of false acceptance, false rejection, correct detection, and repeatability, are reported and conclusions are drawn. |
