Moving object classification using horizontal laser scan data

Motivated by two potential applications, i. e. enhancing driving safety and traffic data collection, a system has been developed using a single-layer horizontal laser scanner as the major sensor for both localization and perception of the surroundings in a large dynamic urban environment. This research focuses on a classification method, that given a stream of laser measurements, classify the moving object into either a person, a group of people, a bicycle or a car. In this research, a number of features are defined after examining the property of data appearance. A classification method is proposed after examining the likelihood measures between each pair of feature and class. Experimental results are presented, demonstrating that the algorithm has efficiency with respect to both driving safety and traffic data collection in highly dynamic environment.

Authors

• Huijing Zhao
• Quanshi Zhang
• Masaki Chiba
• Ryosuke Shibasaki
• Jinshi Cui
• Hongbin Zha

Keywords

• Vehicle dynamics
• Object detection
• Cameras
• Global Positioning System
• Bicycles
• Probes
• Laser radar
• Simultaneous localization and mapping
• Safety
• Roads
• Laser Scanning
• Object Classification
• Laser Scanning Data
• Horizontal Laser
• Classification Methods
• Dynamic Environment
• Safety Data
• Traffic Data
• Feature Pairs
• Pair Of Classes
• Horizontal Axis
• Video Camera
• Valid Estimates
• Major Roads
• Valid Values
• Video Images
• Speed Estimation
• Downtown Area
• Laser Pointer
• Motion Vector
• Speed Of The Object