The representation, recognition, and locating of 3-d objects
International Journal of Robotics Research
Surfaces in range image understanding
Surfaces in range image understanding
From surfaces to objects: computer vision and three dimensional scene analysis
From surfaces to objects: computer vision and three dimensional scene analysis
Object recognition by computer: the role of geometric constraints
Object recognition by computer: the role of geometric constraints
3-D Structures for Generic Object Recognition
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Pictorial Structures for Object Recognition
International Journal of Computer Vision
A stochastic grammar of images
Foundations and Trends® in Computer Graphics and Vision
Learning function-based object classification from 3D imagery
Computer Vision and Image Understanding
| Hi-index | 0.00 |
This paper proposes an object classification framework based on a geometric grammar aimed for mobile robotic applications. The paper first discusses the geometric grammar as a compact representation form for object categories with primitive parts as its constituent elements. The paper then discusses the object classification implemented as parsing of primitive parts. In particular, two approaches are discussed that constrain the search space in order to render the parsing of the primitive parts practical. The two approaches are experimentally verified, first, for a generic object category of chair applied to real range images acquired with a range camera mounted on a mobile robot and, second, for multiple generic object categories applied to synthetic range images. The experimental results show the practicability of the framework.