Real Time Object Pose Estimation by Two-Step Crossing Line Fitting

Abstract

Real-time industrial vision system for object detection and pose estimation is a promising area yet posing a challenge for high processing efficiency. This paper presents a fast object detection and pose estimation method which captures the specific but common visual pattern as contained in many objects – the two-line cross. A two-step grid based scheme is designed, being able to fast detect the crossing line on the objects and thus identifying the object location and pose. Superior efficiency – 4 milliseconds per frame on a laptop with 2.53 HZ is reported for real image data, without any parallelization or hardware acceleration. Our method outperforms the state-of-the-art line detection method significantly, and has been applied in embedded inspection platform for pipeline object pose estimation.

Keywords

• Object pose estimation
• Monocular images
• Crossing line fitting.