Name
Abstract | ||
|---|---|---|
Automatic Number-Plate Recognition (ANPR) system is commonly deployed on the road networks and used in field of safety and security systems. It is interesting to figure out the purpose of each vehicles based on the huge amount of ANPR data captured daily by embedded ANPR cameras. In this paper, we propose spatial and temporal quantitative indicators of vehicle trace features and the extraction algorism. We applied data-mining techniques to analysis vehicle activity patterns from ANPR data, and proposed centroids based activity classification method. Evaluations show the capability and efficiency of the proposed approach. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/EUC.2014.22 | EUC |
Keywords | Field | DocType |
automatic number-plate recognition system,vehicle activity analysis,vehicle,centroids based activity classification method,k-mean,data-mining techniques,vehicle trace features,feature extraction,image classification,anpr system,classification, data mining, k-mean, vehicle,object recognition,data mining,classification,ubiquitous computing | Data mining,k-means clustering,Activity classification,Road networks,Pattern recognition,Computer science,Algorism,Artificial intelligence,Ubiquitous computing,Centroid | Conference |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuyan Sun | 1 | 10 | 3.60 |
| Xinyun Zhou | 2 | 3 | 0.80 |
| Sun Limin | 3 | 467 | 65.09 |
| Shuixian Chen | 4 | 6 | 1.81 |