A Human Detection Framework for Heavy Machinery
Teuvo Heimonen, Janne Heikkilä · 2010
A stereo camera based human detection framework for heavy machinery is proposed. The framework allows easy integration of different human detection and image segmentation methods. This integration is essential for diverge and challenging work machine environments, in which traditional, one detector based human detection approaches has been found to be insufficient. The framework is based on the idea of pixel-wise human probabilities, which are obtained by several separate detection trials following binomial distribution. The framework has been evaluated with extensive image sequences of authentic work machine environments, and it has proven to be feasible. Promising detection performance was achieved by utilizing publically available human detectors.