Semantic fusion of laser and vision in pedestrian detection

Fusion of laser and vision in object detection has been accomplished by two main approaches: 1) independent integration of sensor-driven features or sensor-driven classifiers, or 2) a region of interest (ROI) is found by laser segmentation and an image classifier is used to name the projected ROI. We propose a novel fusion approach based on semantic information, and embodied on many levels. Sensor fusion is based on spatial relationship of parts-based classifiers, being performed via a Markov logic network. The proposed system deals with partial segments, it is able to recover depth information even if the laser fails, and the integration is modeled through contextual information - characteristics not found on previous approaches. Experiments in pedestrian detection is shown in this video.

Category:

Science & Technology

Tags:

• lidar
• laserscanner
• pedestrian detection
• sematic fusion
• vision
• context-aware