Since face recognition from video typically involves two steps: face detection and face recognition, one of the problems associated with poor face recognition results is poor face detection. In the current work, the authors devise a three-step strategy to prune a set of frames in a probe video to that subset in which the face is actually found and in which the matching scores are more reliable.
The authors also exploit temporal continuity of video frames to improve recognition by weighting the match scores based on the results in previously seen frames. The authors show that though this is a very challenging real-world dataset, by combining these different approaches, recognition can improve over the baseline case. (Publisher abstract provided)
Downloads
Similar Publications
- A 10-67-GHz CMOS Dual-Function Switching Attenuator With Improved Flatness and Large Attenuation Range
- DSP Implementation of the Particle Swarm and Genetic Algorithms for Real-Time Design of Thinned Array Antennas
- Profiles of Law Enforcement Agency Body Armor Policies-A Latent Class Analysis of the LEMAS 2013 Data