An hardware architecture for 3D object tracking and motion estimation

We present a method to track and estimate the motion of a 3D object with a monocular image sequence. The problem is based on the state equations and is solved by a sequential Monte Carlo method. The method uses a CAD model of the object whose projection can be compared directly with the pixels of the image. The advantage is to obtain a better accuracy and a direct estimation of the pose and motion in the 3D world. However, this algorithm needs a massive load in computing. For real-time use, we develop in this paper a distributed algorithm that dispatches the processing between the central processing unit (CPU) and the graphics processing unit (GPU) of a consumer-market computer. Some experimental results show that it is possible to obtain an accurate 3D tracking of the object with low computing costs.