Recognition of Partially Occluded Elliptical Objects using Symmetry on Contour

Abstract

There are many research efforts in object recognition. Most existing methods for object recognition are based on full objects. However, many images contain multiple objects with occluded shapes and regions. Due to the occlusion of objects, image retrieval can provide incomplete, uncertain, and inaccurate results. To resolve this problem, we propose a new method to reconstruct objects using symmetry properties since most objects in a given image database are represented by symmetrical figures. Even though there have been several efforts in object recognition with occlusion, current methods have been highly sensitive to object pose, rotation, scaling, and visible portion of occluded objects. In addition, many appearance-based and model-based object recognition methods assumed that they have known occluded regions of objects or images through extensive training processes with statistical approach. However, our new approach is not limited to recognizing occluded objects by pose and scale changes, and does not need extensive training processes. Unlike existing methods, the proposed method finds shapes and regions to reconstruct occluded shapes and regions within objects. We assume that we only consider the elliptical objects in recognition. The proposed approach can handle object rotation and scaling for dealing with occlusion, and does not require extensive training processes. The main advantage of our proposed approach is that it becomes simple to reconstruct objects from occlusions using symmetry. We present a robust method, which is based on the contours of objects, for recognizing partially occluded objects based on symmetry properties. The contour-based approach finds a symmetry axis using the maximum diameter from the occluded object. In experiments, we demonstrate how a proposed method reconstructs and recognizes occluded shapes and regions using symmetry. Experiments use rotated and scaled objects for dealing with occlusion. We use mirror symmetry to find possible occluded regions in objects. Examples of partially occluded objects are shown in Figure 1.1. We also evaluate the recognition rate of the reconstructed objects using symmetry and the visible portion of the occluded objects for recognition. The method produces average recognition rates for cups and plates above 88% with 30% occlusion. In this case, part of the