| Paper: | WP-L6.7 |
| Session: | Object Recognition II |
| Time: | Wednesday, September 19, 16:50 - 17:10 |
| Presentation: |
Lecture
|
| Title: |
NIGHTTIME PEDESTRIAN DETECTION WITH NEAR INFRARED USING CASCADED CLASSIFIERS |
| Authors: |
Jianfei Dong; Tsinghua University | | |
| | Junfeng Ge; Tsinghua University | | |
| | Yupin Luo; Tsinghua University | | |
| Abstract: |
This paper presents a novel nighttime pedestrian detection approach only using a near infrared camera, which can be used in a practical driver assistance systems. This method can be divided into three steps: selection step, preprocess step and recognition step. Firstly, objects in the video are separated with an adaptive dual thresholds segmentation method in the selection step; Secondly, most of non-pedestrians are discarded with some constraints in thepreprocess step; Finally, in the recognition step a cascaded classifiers with Histograms of Oriented Gradients and Adaptive Boosting Algorithm are introduced. Experiments on video sequences show that the proposed pedestrian detection approach has a high detection rate as well as a very low false alarm rate and run in real-time. |
