Abstract
Detecting pedestrians is still a challenging task for automotive vision system
due the extreme variability of targets, lighting conditions, occlusions, and
high speed vehicle motion. A lot of research has been focused on this problem
in the last 10 years and detectors based on classifiers has gained a special
place among the different approaches presented. This work presents a
state-of-the-art pedestrian detection system based on a two stages classifier.
Candidates are extracted with a Haar cascade classifier trained with the
DaimlerDB dataset and then validated through part-based HOG classifier with the aim of lowering the number of false positives. The surviving candidates
are then filtered with a feature-based tracking to enhance the recognition robustness and improve the results' stability. The system has been implemented on a prototype vehicle and offers high performance in terms of
several metrics, such as detection rate, false positives per hour, and frame
rate. The novelty of this system rely in the combination of HOG part-based approach, tracking based on specific optimized feature and porting on a real prototype.
due the extreme variability of targets, lighting conditions, occlusions, and
high speed vehicle motion. A lot of research has been focused on this problem
in the last 10 years and detectors based on classifiers has gained a special
place among the different approaches presented. This work presents a
state-of-the-art pedestrian detection system based on a two stages classifier.
Candidates are extracted with a Haar cascade classifier trained with the
DaimlerDB dataset and then validated through part-based HOG classifier with the aim of lowering the number of false positives. The surviving candidates
are then filtered with a feature-based tracking to enhance the recognition robustness and improve the results' stability. The system has been implemented on a prototype vehicle and offers high performance in terms of
several metrics, such as detection rate, false positives per hour, and frame
rate. The novelty of this system rely in the combination of HOG part-based approach, tracking based on specific optimized feature and porting on a real prototype.
| Original language | English |
|---|---|
| Title of host publication | 15th International Conference on Intelligent Transportation Systems |
| Publisher | IEEE |
| Publication date | 16 Sept 2012 |
| Pages | 73 - 77 |
| ISBN (Print) | 978-1-4673-3064-0 |
| DOIs | |
| Publication status | Published - 16 Sept 2012 |
| Event | Intelligent Transportation Systems Conference - Anchorage, United States Duration: 16 Sept 2012 → 19 Sept 2012 Conference number: 15 |
Conference
| Conference | Intelligent Transportation Systems Conference |
|---|---|
| Number | 15 |
| Country/Territory | United States |
| City | Anchorage |
| Period | 16/09/2012 → 19/09/2012 |