For intelligent vehicle applications, detecting pedestrian technique must be robust and perform in real time. In pedestrian detection, support vector machine (SVM) is one of the popular classifiers because of its robust performance. In this paper, we propose the new method to implement cascade SVM that enables fast rejection of negative samples. The proposed method is tested with INRIA person dataset and show better rejection performance of negative samples than conventional method.
|Title of host publication||2015 International Joint Conference on Neural Networks, IJCNN 2015|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|ISBN (Electronic)||9781479919604, 9781479919604, 9781479919604, 9781479919604|
|Publication status||Published - 2015 Sep 28|
|Event||International Joint Conference on Neural Networks, IJCNN 2015 - Killarney, Ireland|
Duration: 2015 Jul 12 → 2015 Jul 17
|Name||Proceedings of the International Joint Conference on Neural Networks|
|Other||International Joint Conference on Neural Networks, IJCNN 2015|
|Period||15/7/12 → 15/7/17|
Bibliographical notePublisher Copyright:
© 2015 IEEE.
All Science Journal Classification (ASJC) codes
- Artificial Intelligence