Abstract | ||
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This paper proposes a velocity learning method based on the directional Gaussian model to detect speeding events in surveillance scenarios. The proposed method is of an uncalibrated type, but yet has considered the influences of projective transformation on estimating the motion velocities in an image plane, which is convenient and feasible to use in real application. We have analyzed the theory t... |
Year | DOI | Venue |
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2017 | 10.1109/TIFS.2017.2705623 | IEEE Transactions on Information Forensics and Security |
Keywords | Field | DocType |
Event detection,Surveillance,Security,Computational modeling,Analytical models,Forensics,Videos | Computer vision,Computer science,Image plane,Surface fitting,Homography,Gaussian network model,Artificial intelligence,Sampling (statistics) | Journal |
Volume | Issue | ISSN |
12 | 10 | 1556-6013 |
Citations | PageRank | References |
2 | 0.35 | 31 |
Authors | ||
5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Jiajun Wen | 1 | 113 | 11.63 |
Zhihui Lai | 2 | 1204 | 76.03 |
Zhong Ming | 3 | 1377 | 106.41 |
W K Wong | 4 | 151 | 16.60 |
Zhong Zuofeng | 5 | 62 | 4.56 |