TY - GEN
T1 - Human detection in low resolution thermal images based on combined HOG classifier
AU - Budzan, Sebastian
N1 - Publisher Copyright:
© Springer International Publishing AG 2016.
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/84989863205
U2 - 10.1007/978-3-319-46418-3_27
DO - 10.1007/978-3-319-46418-3_27
M3 - Conference contribution
AN - SCOPUS:84989863205
SN - 9783319464176
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 304
EP - 315
BT - Computer Vision and Graphics - International Conference, ICCVG 2016, Proceedings
A2 - Datta, Amitava
A2 - Wojciechowski, Konrad
A2 - Chmielewski, Leszek J.
A2 - Kozera, Ryszard
PB - Springer Verlag
T2 - International Conference on Computer Vision and Graphics, ICCVG 2016
Y2 - 19 September 2016 through 21 September 2016
ER -