Real-time object tracking for moving target auto-focus in digital camera

Focusing at a moving object accurately is difficult and important to take photo of the target successfully in a digital camera. Because the object often moves randomly and changes its shape frequently, position and distance of the target should be estimated at real-time so as to focus at the objet precisely. We propose a new method of real-time object tracking to do auto-focus for moving target in digital camera. Video stream in the camera is used for the moving target tracking. Particle filter is used to deal with problem of the target object’s random movement and shape change. Color and edge features are used as measurement of the object’s states. Parallel processing algorithm is developed to realize real-time particle filter object tracking easily in hardware environment of the digital camera. Movement prediction algorithm is also proposed to remove focus error caused by difference between tracking result and target object’s real position when the photo is taken. Simulation and experiment results in digital camera demonstrate effectiveness of the proposed method. We embedded real-time object tracking algorithm in the digital camera. Position and distance of the moving target is obtained accurately by object tracking from the video stream. SIMD processor is applied to enforce parallel real-time processing. Processing time less than 60ms for each frame is obtained in the digital camera with its CPU of only 162MHz.

[1]  Luc Van Gool,et al.  An adaptive color-based particle filter , 2003, Image Vis. Comput..

[2]  Neil J. Gordon,et al.  A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..

[3]  Branko Ristic,et al.  A particle filter for joint detection and tracking of color objects , 2007, Image Vis. Comput..

[4]  Dorin Comaniciu,et al.  Kernel-Based Object Tracking , 2003, IEEE Trans. Pattern Anal. Mach. Intell..