Human Detection in Low Resolution Thermal Images Based on Combined HOG Classifier

摘要

The human detection in real environment is important task of the computer vision, especially if we take into account thermal imagery. Most of the recent methods are based on the low-level features or body parts detection or combination. Method proposed in this paper uses combination of modified Histogram of Oriented Gradients (HOG) with detection of the human head. The minimal distance classifier has been used to improve the reduction of the human candidates process. The experiments have been performed on thermal images taken in real environment in different scenario such as missing body parts, overlapped people, different pose, far and near distance to the human, small groups of people, large groups of the people. The performance of the proposed algorithm has been evaluated using Precision and Recall quality measure with comparison to the selected reference methods.