Grouping method based on feature matching for tracking and recognition of complex objects

We propose a grouping algorithm for tracking and recognition of complex objects in video images. The algorithm is based on region-growing image segmentation for dividing each image into its constituent elements or segments and feature matching using the characteristic features of these elements. All segments in video images, which can be viewed as simple objects, can be detected and tracked with this algorithm no matter whether they are moving or not. But, for complex-object tracking and recognition, it is additionally necessary to group all elements belonging to these complex objects based on common characteristic features. As a result of the grouping method, the proposed algorithm is able to detect and track moving complex objects like e.g. cars in video images. This paper describes the proposed algorithm in detail and verifies its capabilities by simulation results with MATLAB [1].