CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Automatic Face Recognition for Film Character Retrieval in Feature-Length Films
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Evaluating Multi-Object Tracking
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Person Reidentification Using Spatiotemporal Appearance
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Machine Vision and Applications
Video parsing based on head tracking and face recognition
Proceedings of the 6th ACM international conference on Image and video retrieval
Evaluating multiple object tracking performance: the CLEAR MOT metrics
Journal on Image and Video Processing - Regular
A brief introduction to boosting
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Open-Set Face Recognition-Based Visitor Interface System
ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
Face alignment by minimizing the closest classification distance
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
A video-based door monitoring system using local appearance-based face models
Computer Vision and Image Understanding
Robust precise eye location under probabilistic framework
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Person spotting: video shot retrieval for face sets
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
People reidentification in surveillance and forensics: A survey
ACM Computing Surveys (CSUR)
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In this paper, we present a system for person re-identification in TV series. In the context of video retrieval, person re-identification refers to the task where a user clicks on a person in a video frame and the system then finds other occurrences of the same person in the same or different videos. The main characteristic of this scenario is that no previously collected training data is available, so no person-specific models can be trained in advance. Additionally, the query data is limited to the image that the user clicks on. These conditions pose a great challenge to the re-identification system, which has to find the same person in other shots despite large variations in the person's appearance. In the study, facial appearance is used as the re-identification cue, since, in contrast to surveillance-oriented re-identification studies, the person can have different clothing in different shots. In order to increase the amount of available face data, the proposed system employs a face tracker that can track faces up to full profile views. This makes it possible to use a profile face image as query image and also to retrieve images with non-frontal poses. It also provides temporal association of the face images in the video, so that instead of using single images for query or target, whole tracks can be used. A fast and robust face recognition algorithm is used to find matching faces. If the match result is highly confident, our system adds the matching face track to the query set. Finally, if the user is not satisfied with the number of returned results, the system can present a small number of candidate face images and lets the user confirm the ones that belong to the queried person. These features help to increase the variation in the query set, making it possible to retrieve results with different poses, illumination conditions, etc. The system is extensively evaluated on two episodes of the TV series Coupling, showing very promising results.