IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Panoramic representation for route recognition by a mobile robot
International Journal of Computer Vision - Special issue on machine vision research at Osaka University
Active and exploratory perception
CVGIP: Image Understanding - Special issue on purposive, qualitative, active vision
Panoramic vision
Creating Image-Based VR Using a Self-Calibrating Fisheye Lens
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Catadioptric Omnidirectional Camera
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Mosaic based representations of video sequences and their applications
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Multidirectional Stereovision Sensor, Calibration and Scenes Reconstruction
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Surface image synthesis of moving spinning cans using a 1,000-fps area scan camera
Machine Vision and Applications - Integrated Imaging and Vision Techniques for Industrial Inspection
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Many computer vision applications can benefit from omnidirectional vision sensing, rather than depending solely on conventional cameras that have constrained fields of view. For example, mobile robots often require a full 360° view of their environment in order to perform navigational tasks such identifying landmarks, localizing within the environment, and determining free paths in which to move. There has been much research interest in omnidirectional vision in the past decade and many techniques have been developed. These techniques include: (i) catadioptric methods which can provide rapid image acquisition, but lack image resolution; and (ii) mosaicing and linear scanning techniques which have high image resolution but typically have slow image acquisition speed. In this paper, we introduce a novel linear scanning panoramic vision system that can acquire panoramic images quickly with little loss of image resolution. The system makes use of a fast line-scan camera, instead of a slower, conventional area-scan camera. In addition, a unique coarse-to-fine panoramic imaging technique has been developed that is based on smart sensing principles. Using the active vision paradigm, we control the motion of the rotating camera using feedback from the images. This results in high acquisition speeds and proportionally low storage requirements. Experimentation has been carried out, and results are given.