Example-Based Learning for View-Based Human Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Boosting Chain Learning for Object Detection
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Robust Object Detection via Soft Cascade
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Detection filters and algorithm fusion for ATR
IEEE Transactions on Image Processing
Performance characterization of the dynamic programming obstacle detection algorithm
IEEE Transactions on Image Processing
A cascaded method to detect aircraft in video imagery
International Journal of Robotics Research
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An application of the Viola and Jones object detector to the problem of aircraft detection is presented. This approach is based on machine learning rather than morphological filtering which was mainly used in previous works. Aircraft detection using computer vision methods is a challenging problem since target aircraft can vary from subpixels to a few pixels in size and the background can be heavily cluttered. Such a system can be a part of a collision avoidance system to warn the pilots of potential collisions. Initial results suggest that this (static) approach on a frame to frame basis achieves a detection rate of about 80% and a false positive rate which is comparable with other approaches that use morphological filtering followed by a tracking stage. The system was evaluated on over 15000 frames which were extracted from real video sequences recorded by NASA and has the potential of real time performance.