A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Panoramic Virtual Stereo Vision of Cooperative Mobile Robots for Localizing 3D Moving Objects
OMNIVIS '00 Proceedings of the IEEE Workshop on Omnidirectional Vision
Self-localization in non-stationary environments using omni-directional vision
Robotics and Autonomous Systems
Development of a virtual reality GIS using stereo vision
Computers and Electronics in Agriculture
Personnel tracking on construction sites using video cameras
Advanced Engineering Informatics
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Fast construction of dynamic and multi-resolution 360° panoramas from video sequences
Image and Vision Computing
Probabilistic structure matching for visual SLAM with a multi-camera rig
Computer Vision and Image Understanding
Collision sensing by stereo vision and radar sensor fusion
IEEE Transactions on Intelligent Transportation Systems
Depth-based target segmentation for intelligent vehicles: fusion of radar and binocular stereo
IEEE Transactions on Intelligent Transportation Systems
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It is critical to detect and identify obstacles for safe operation of robot tractors. This study focused on human detection using an omni-directional stereo vision (OSV). The Lucas-Kanade optical flow detection method was used to detect human in a panoramic image. A 3D panoramic image that was reconstructed from stereo rectified images using the sum of squared differences (SSDs) method was used to locate the position of a human. To evaluate the performance of the developed human detection method, two RTK-GPSs were used to investigate the accuracy of the detection method under stationary and motion conditions of a robot tractor. The results of field experiments indicated that a human could be detected successfully under both given conditions in the daytime. The RMS error of measured distance was less than half a meter compared with the reference distance measured by the RTK-GPSs.