Title :
Visual framing feedback for desktop video conferencing
Author :
Wu, Chen ; Samadani, Ramin ; Mitchell, April ; Baker, Mary ; Gelb, Dan
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA
Abstract :
Desktop video conferencing participants are often poorly positioned in their outgoing video - unaware of their appearance on camera. We combine face detection, feature tracking and motion detection for automatic real-time detection of poorly framed participants and subsequently provide framing feedback by compositing their incoming and outgoing video streams. Our solution provides participants visual feedback only while they have framing problems. Otherwise the display shows only the remote participants, allowing users to focus fully on the conference. We analyze the system components and describe a user study that found advantages of our approach over the existing mirror window solution.
Keywords :
face recognition; feature extraction; image motion analysis; microcomputers; object detection; object tracking; teleconferencing; video communication; video streaming; desktop video conferencing participants; face detection; feature tracking; mirror window solution; motion detection; participants visual feedback; poorly framed participant detection; video streams; visual framing feedback; Face; Face detection; Feature extraction; Mirrors; Motion detection; Streaming media; Tracking; video analysis; video conferencing;
Conference_Titel :
Image Processing (ICIP), 2011 18th IEEE International Conference on
Conference_Location :
Brussels
Print_ISBN :
978-1-4577-1304-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2011.6116275