Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : May 27, 2020 - May 30, 2020
In recent years, in object tracking of expecting the children’s monitoring and the automotive applications, modeling the motion of a tracked object is an important task for determining the performance of the tracking algorithm. If there is no prior knowledge about the motion of a target, it often tracks it with a particle filter under the assumption of “ smooth motion. ”Note however that, this doesn’t work well for sudden movement changes and unexpected movements, and fails to track them. Thus, a system has been already developed to model the motion of a tracked object by optical flow and track it with a particle filter. The Lucas and Kanade (LK) method is known as a typical algorithm that acquires the optical flow. In this method, the brightness is assumed to be preserved such that the brightness value in the same pixel doesn’t change between frames. However, the brightness preservation is not held in reality due to noises caused by the change of the photography environment and the change of amount of solar radiation. In this paper, an algorithm for estimating the optical flow, which is robust against luminance changes, is developed by calculating the amount of luminance changes with the difference average and by correcting the temporal luminance gradient. In addition, some experiments on object tracking are conducted using an optical flow–based particle filter that is robust to luminance changes, so that its effectiveness is verified through such experiments.
