Name
Abstract | ||
|---|---|---|
In this paper, an intelligent sensor network is developed for object detection, classification and recognition. We utilize wireless sensors as the first layer to detect coordinates of moving objects in a secured area. Cameras are activated to capture image features for object classification and recognition. In order to reduce processing time, a hierarchical image extraction approach is developed. Global object features such as size and motion are acquired for classifying objects into a number of classes. If the moving object is considered suspicious, the cameras will be requested to capture detailed images for object recognition. Experimental results show that our system can achieve a high face recognition rate of 95.4% for the testing images captured by the surveillance system. |
Year | Venue | Keywords |
|---|---|---|
2007 | JOURNAL OF INFORMATION SCIENCE AND ENGINEERING | surveillance system,sensor networks,support vector machine,pattern recognition,image processing |
Field | DocType | Volume |
Computer vision,Object detection,Viola–Jones object detection framework,3D single-object recognition,Object-class detection,Computer science,Visual sensor network,Haar-like features,Artificial intelligence,Contextual image classification,Cognitive neuroscience of visual object recognition | Journal | 23 |
Issue | ISSN | Citations |
6 | 1016-2364 | 0 |
PageRank | References | Authors |
0.34 | 12 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Frank Y. Shih | 1 | 1103 | 89.56 |
| Yi-Ta Wu | 2 | 331 | 31.22 |
| Chao-fa Chuang | 3 | 218 | 10.82 |
| Jiann-Liang Chen | 4 | 371 | 55.13 |
| Hsi-Feng Lu | 5 | 21 | 3.11 |
| Yao-Chung Chang | 6 | 72 | 10.58 |