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This paper presents a system that can efficiently detect objects and estimate their 6D postures with RGB-D and motion sensor data on a mobile device. We apply a template-based method to detect the pose of an object, in which the matching process is accelerated through dimension reduction of the vectorized template matrix. After getting the initial pose, the proposed system then tracks the detected objects by a modified bidirectional iterative closest point algorithm. Furthermore, our system checks information from the inertial measurement unit on a mobile device to alleviate intensive computation for ease of interactive applications.

Efficient Recognition and 6D Pose Tracking of Markerless Objects with RGB-D and Motion Sensors on Mobile Devices