The Randomized Hough Transform (RHT) is originally a method for finding global features from an image. These features can be curve segments like line segments, circles, ellipses etc. However, the RHT can also be applied to motion estimation. The new algorithm, called Motion Detection Using the Randomized Hough Transform (MDRHT), can be used for solving machine vision problems like tracking of moving objects.
The MDRHT is an efficient and simple 2-D motion detection method. Moving objects are assumed to be rigid and a number of moving objects to be unknown. Objects can be partially non-rigid or distorted.
There are moving objects in the gray-level image sequence shown below. Consecutive image frames are examined frame by frame. Using edge points of gray-level pictures, translational motion of moving objects is estimated. Motion is detected first, and only after that objects are segmented for tracking and recognition. The result of applying the MDRHT in first two frames is shown in the last picture. Two moving objects are found.

Nature of work: Basic Research Realization: Heikki Kälviäinen, 1990-1994
Lei Xu, Erkki Oja,
Partners: Lappeenranta University Finance: Academy of Finland
of Technology