Abstract
We systematically investigate how geometric constraints can be used for efficient sliding-window object detection. Starting with a general characterization of the space of sliding-window locations that correspond to geometrically valid object detections, we derive a general algorithm for incorporating ground plane constraints directly into the detector computation. Our approach is indifferent to the choice of detection algorithm and can be applied in a wide range of scenarios. In particular, it allows to effortlessly combine multiple different detectors and to automatically compute regions-of-interest for each of them. We demonstrate its potential in a fast CUDA implementation of the HOG detector and show that our algorithm enables a factor 2-4 speed improvement on top of all other optimizations.
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Sudowe, P., Leibe, B. (2011). Efficient Use of Geometric Constraints for Sliding-Window Object Detection in Video. In: Crowley, J.L., Draper, B.A., Thonnat, M. (eds) Computer Vision Systems. ICVS 2011. Lecture Notes in Computer Science, vol 6962. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23968-7_2
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DOI: https://doi.org/10.1007/978-3-642-23968-7_2
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