Structure and motion recovery using two step sampling for 3D match move

Abstract

Camera pose and scene geometry estimation is a fundamental requirement for match move to insert synthetic 3D objects in real scenes. In order to automate this process, auto-calibration that estimates the camera motion without prior calibration information is needed. Most auto-calibration methods for multi-views contain bundle adjustment or non-linear minimization process that is complex and difficult problem. This paper presents two methods for recovering structure and motion from handheld image sequences: the one is key-frame selection, and the other is to reject the frame with large errors among key-frames in absolute quadric estimation by LMedS (Least Median of Square). The experimental results showed the proposed method can achieve precisely camera pose and scene geometry estimation without bundle adjustment.