Generic Object Recognition Using CAD-Based Multiple Representat ions
نویسندگان
چکیده
Real-world applications of computer vision usually involve a variety of object models making a single model representation somewhat inadequate for object recognition. Multiple representations, on the other hand, allow different matching strategies to be applied for the same object, or even for different parts of the same object. This paper is concerned with the use of CAD-derived hierarchical models having multiple representations concave/convex edges and straight homogeneous generalized cylinder for generic object recognition in outdoor visible imagery. It also presents a refocused matching algorithm that uses a hierarchically structured model database to facilitate generic object recognition. Experimental results demonstrating generic recognition of objects in perspective, aerial images are presented.
منابع مشابه
Decoupling Recognit ion and Localization in CAD-Based Vision
Many CAD-based recognition systems have relied on accurate pose estimation and back-projection in order to verify weak correspondences between simple image and model features. This coupling of recognition and localization requires object models which capture the exact geometry of the object, precluding the recognilion of generic objects in less restricted domains. In this paper, we synthesize a...
متن کاملGeneric object recognition using multiple representations
Real-world image understanding tasks often involve complex object models which are not adequately represented by a single representational scheme for the various recognition scenarios encountered in practice. Multiple representations, on the other hand, allow different matching strategies to be applied for the same object, or even for different parts of the same object. This paper is concerned ...
متن کاملAdaptive Performance-Based Classifier Combination for Generic Object Recognition
It is well-established in the pattern recognition community that the performance of classifiers can be greatly improved by combining the outputs of multiple classifiers. In this paper, we introduce the concept of adaptive performance-based classifier combination, i.e., the weighting of classifiers based on their estimated recognition performance, to generic object recognition. Using an expectat...
متن کاملThree-dimensional visualization environment for multisensor data analysis, interpretation, and model-based object recognition
Model-based object recognition must solve three-dimensional geometric problems involving the registration of multiple sensors and the spatial relationship of a three-dimensional model to the sensors. Observation and verification of the registration and recognition processes requires display of these geometric relationships. We have developed a prototype software system which allows a user to in...
متن کاملApplication of Combined Local Object Based Features and Cluster Fusion for the Behaviors Recognition and Detection of Abnormal Behaviors
In this paper, we propose a novel framework for behaviors recognition and detection of certain types of abnormal behaviors, capable of achieving high detection rates on a variety of real-life scenes. The new proposed approach here is a combination of the location based methods and the object based ones. First, a novel approach is formulated to use optical flow and binary motion video as the loc...
متن کامل