Face Tracking in Meeting Room Scenarios Using Omnidirectional Views
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Instantaneous robot self-localization and motion estimation with omnidirectional vision
Robotics and Autonomous Systems
Multispectral image data fusion using POCS and super-resolution
Computer Vision and Image Understanding
Superresolution modeling using an omnidirectional image sensor
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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The catadioptric omnidirectional sensor, called Omni-Vision, involving capture and automatic interpretation of images, depicts full horizontal panorama 360 degrees view of the surroundings. The field of view band can be easily transformed to a panoramic image and a converntional perspective image. However, it has an intrinsical disadvantage that the angular resolution Omni-Vision is lower than that of conventional video camera. In this paper, a super-resolution method for the Omni-Vision is proposed to reconstruct high resolution panoramic transformed images, in which consecutive images obtained by rotating motion of Omni-Vision are fused using the POCS (project on convex sets) algorithm. Experiment results are also provided to demonstrate the efficiency of the proposed method.