In this paper, we propose a novel multi-class graph boosting algorithm to recognize different visual objects. The proposed method treats subgraph as feature to construct base clas...
Bang Zhang, Getian Ye, Yang Wang 0002, Wei Wang, J...
In this paper, we present an efficient algorithm for 3D object recognition in presence of clutter and occlusions in noisy, sparse and unsegmented range data. The method uses a robu...
This paper proposes a model-based methodology for recognizing and tracking objects in digital image sequences. Objects are represented by attributed relational graphs (or ARGs), w...
When objects are recognized by using multiple cameras, recognition rates strongly depend on the camera arrangement. In this paper, we propose a new method for planning a multiple ...
In this paper, we propose novel blur and similarity transform (i.e. rotation, scaling and translation) invariant features for the recognition of objects in images. The features ar...