Object detection in traffic scenes by a colour video and radar data fusion approach
- 24 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
Object detection is one of the key functions in autonomous driving. For this purpose different sensor types-such as laser or millimeter-wave (MMW) radar-are in use but most systems are solely based on vision (Thomanek et al., 1994). In contrast, this paper presents a data fusion approach for joint radar video object detection.Keywords
This publication has 9 references indexed in Scilit:
- Obstacle detection by real-time optical flow evaluationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- 3-D Image Recognition System For Drive AssistPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Multiple object recognition and scene interpretation for autonomous road vehicle guidancePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Towards all around automatic visual obstacle sensing for carsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Vision-based car-following: detection, tracking, and identificationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Millimeter-wave imaging of traffic scenariosPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- One-pass encoding of connected components in multivalued imagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Obstacle detection based on color blob flowPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Image Segmentation Improvement with a 3-D Microwave RadarPublished by Springer Nature ,1993