Recognition of Partially Occluded Objects Using B-tree Index Structure: An Efficient and Robust Approach
نویسندگان
چکیده
This paper presents a novel method for recognizing partially occluded objects. The proposed method uses corner points and their spatial relationship perceived through the application of Triangular Spatial Relationship (TSR) [5] by considering three successive corner points at a time. The perceived TSR among corner points are used to create a model object-base using B-tree, an efficient multilevel indexing scheme. The matched sequence is preserved in a two-dimensional matrix called status matrix. Experimental results, on real images of varying complexity of a reasonably large database of objects have established the robustness of the method.
منابع مشابه
Interpretation of complex scenes using dynamic tree-structure Bayesian networks
This paper addresses the problem of object detection and recognition in complex scenes, where objects are partially occluded. The approach presented herein is based on the hypothesis that a careful analysis of visible object details at various scales is critical for recognition in such settings. In general, however, computational complexity becomes prohibitive when trying to analyze multiple su...
متن کاملRecognition of Partially Occluded Elliptical Objects using Symmetry on Contour
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 symm...
متن کاملRobust 3-dimensional object recognition using stereo vision and geometric hashing
We propose a technique that combines geometric hashing with stereo vision. The idea is to use the robustness of geometric hashing to spurious data to overcome the correspondence problem, while the stereo vision setup enables direct model matching using the 3-D object models. Furthermore, because the matching technique relies on the relative positions of local features, we should be able to perf...
متن کاملInterpretation of Complex Scenes Using Dynamic Tree-Structure Belief Networks
In this paper, we address the problem of object detection and recognition in complex scenes, where objects are partially occluded. We speculate that a careful analysis of visible object details at various scales may prove critical for recognition in these settings. However, in general, computational complexity becomes prohibitive when trying to analyze multiple sub-parts of multiple objects in ...
متن کاملRecognition of Occluded Objects by Local Feature Sequencing
We present a new method for 2-D occluded-object recognition. In this method, objects are segmented then represented by local and (rotation-translation) invariant feature-vectors. A decision tree is used to match similar local features, which allows an efficient and complete selection of potential models. In order to validate each potential model, we explore the geometric relationships between f...
متن کامل