Model-Based 3D Object Tracking Using Projective Invariance

This paper describes a method of 3D object tracking by projective invariance. Usually, projective invariance has been used for object recognition and its property discards the need for cumbersome camera calibration to obtain metric information. We focus on the fact the projective invariance is not only regarded as recognition cues but also able to verify, the status of a 3D object for visual tracking. With projective invariance relevant to points, we develop a fast and reliable visual tracking strategy by combining a recognition module using projective invariance, window-based corner trackers for object's center tracking and a visibility checking module. The proposed method is experimented in single IBM-PC platform successfully.

Authors

• Sung-Woo Lee
• Bum-Jae You
• Gregory D. Hager

Keywords

• Object oriented modeling
• Cameras
• Optical filters
• Calibration
• Image motion analysis
• Target tracking
• Intelligent systems
• Intelligent control
• Control systems
• Computer science
• Object Tracking
• Projective Invariant
• Object Recognition
• Three-dimensional Objects
• Reliable Tracking
• Computational Efficiency
• Invertible
• Tracking System
• Image Plane
• Kalman Filter
• Line Segment
• Target Object
• Optical Flow
• Pose Estimation
• Complex Background
• Camera Frame
• Structural Invariance
• Hough Transform
• State Tracking