Camera array for model reconstruction and pose estimation
(K. H. Wong)

The aim of this research is to investigate how to utilize an array of low cost cameras for model reconstruction and pose estimation. The input of the system is a set of cameras and the output is the 3D model of the objects being viewed and the pose of the cameras. The results are useful for virtual walkthrough system, robot navigation and 3D computer game development. The problem has been investigated by many researchers before; however applying an array of cameras (8 x 8 or more, arranged on a 1 meter square plane) is relatively new. Fundamentally, we believe utilizing the camera array we can provide a solution to the occlusion problem in computer vision. For example, if some of the cameras are blocked, the others can fill in the information. Mathematical methods for a single camera of camera pairs can be extended for a camera array and we propose the following formulations. (1) Extend the traditional formulations, such as the fundamental matrix or trifocal tensor, to an array of cameras, (2) Use of a tracking method (Kalman filtering) for the multiple image sequences obtained by the camera array. Since China is major manufacturing base of low cost digital cameras, our work in using camera arrays can become a lucrative new product line for our computer manufacturing and trading business. A robot with four cameras onboard for our test -- the pose position of the robot (pose) in an environment can be robustly estimated by using the images of the cameras only.