We consider object recognition as the process of attaching meaningful labels to specific regions of an image, and propose a model that learns spatial relationships between objects....
Despite recent successes, pose estimators are still somewhat fragile, and they frequently rely on a precise knowledge of the location of the object. Unfortunately, articulated obj...
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...
The formal description of the semantics of object-oriented data models is still an open problem. Some characteristic features of object-oriented data models, such as methods and i...
This paper presents a distributed object model MOIDE for solving irregularly structured problems on cluster. The primary appeal of MOIDE is its flexible system structure that is a...