Name
Title | ||
|---|---|---|
Global optimization in discretized parameter space for predefined object segmentation |
Abstract | ||
|---|---|---|
In object segmentation field, while the non-predefined object segmentation distinguishes arbitrary self-assumed object from background, predefined object segmentation pre-specifies object evidently. This paper presents a new method to segment predefined objects by globally optimizing an orientation-based objective function that measures the fitness of object boundary in a discretized parameter space. A specific object is explicitly described by normalized discrete sets of boundary points and corresponding normal vectors with respect to its plane shapes in a certain aspect. The orientation factor provides robust distinctness for target objects. By considering the order relation of transformation elements, and their dependency on derived over-segmentation outcome, the domain of translations and scales is discretized efficiently. The appropriate transformation parameters of a shape model corresponding to a target object in an image are determined using the global optimization algorithm branch-bound. Discrete boundary points of the consequent transformed model are chained together to produce the final contour of the target object. The results tested on PASCAL dataset show a considerable achievement in solving complex background and unclear boundary images. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2448556.2448637 | ICUIMC |
Keywords | Field | DocType |
segment predefined object,global optimization,object boundary,arbitrary self-assumed object,boundary point,predefined object segmentation pre-specifies,discrete boundary point,specific object,discretized parameter space,object segmentation field,non-predefined object segmentation,target object,branch bound | Discretization,Scale-space segmentation,Computer science,Segmentation-based object categorization,Real-time computing,Parameter space,Artificial intelligence,Computer vision,Branch and bound,Global optimization,Segmentation,Algorithm,Axis-aligned object | Conference |
Citations | PageRank | References |
0 | 0.34 | 17 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huy Hoang Nguyen | 1 | 2 | 1.84 |
| Hyuk-Ro Park | 2 | 21 | 5.53 |
| Joon Seub Cha | 3 | 0 | 0.34 |
| Le Thi Khue Van | 4 | 0 | 0.68 |
| Gueesang Lee | 5 | 208 | 52.71 |