Recognizing objects from images becomes a more and more important research and application topic. There are diverse applications such as face recognition, analysis of aerial images from multicopters, object tracking, image-based web search, etc. Many existing approaches focus on shape retrieval from a single polygon of contour points, or they try to compare clouds of interesting points of an object. However, human object recognition concentrates on few points of the segments forming the object. Clearly, complex objects, strictly speaking the projections of their shape on the image plain, consist of several (polygonal) segments. Therefore, the procedure presented in this paper takes this into account, by composing objects hierarchically into a group of segments. We briefly introduce our procedure for semantic object recognition based on clusters of image segment contours and discuss the problem of recognizing objects from different perspectives.
['Falk Schmidsberger', 'Frieder Stolzenburg']
Semantic Object Recognition with Segment Faces