TY  - JOUR
T1  - Study of Haar AdaBoost (VJ) and HOG AdaBoost (PoseInv) Detectors for People Detection
AU - OULD TALEB, Nagi AU - Mint Aboubekrine, Aicha AU - Farouk NANNE, Mohamedade AU - BEN MAATI, Mohamed Larbi 
JO  - International Journal of Soft Computing
VL  - 16
IS  - 6
SP  - 134
EP  - 147
PY  - 2021
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2021.134.147
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2021.134.147
KW  - learned-based methods
KW  -Pedestrian detection
KW  -behavior analysis
AB  - The detection of objects in general and
pedestrians in particular in images and videos is a very
popular research topic within the computer vision
community, it is an issue that is currently at the heart of
much research. In this study, we will present a
comparative study of the performance of the two detectors
Haar AdaBoost and HOG AdaBoost in detecting people
in the INRIA image database of people. An evaluation of
the experiments will be presented after making certain
modifications to the detection parameters.
ER  -