Name
Title | ||
|---|---|---|
Extracting Recurrent Motion Flows from Crowded Scene Videos: A Coherent Motion-Based Approach |
Abstract | ||
|---|---|---|
In this paper, we propose a new approach which utilizes coherent motion regions to extract and visualize recurrent motion flows in crowded scene surveillance videos. The proposed approach first extract coherent motion regions from a crowded scene video. Then a frame-level clustering process is proposed to cluster frames into different recurrent-motion-pattern (RMP) groups according to the coherent-region similarity between frames. By merging similar coherent regions from the same RMP group, we can achieve motion flow regions representing the major motion flows in each recurrent motion pattern. Finally, a flow curve extraction process is also proposed which extracts flow curves from motion flow regions to provide a proper visualization of the recurrent motion patterns. Experimental results demonstrate that our approach can precisely achieve recurrent motion flows for various crowded scene videos. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/BigMM.2015.20 | BigMM |
Keywords | Field | DocType |
Coherent motion, Traffic flow extraction, Crowded scene | Structure from motion,High-definition video,Computer vision,Visualization,Computer science,Feature extraction,Artificial intelligence,Motion estimation,Cluster analysis,Trajectory,Semantics | Conference |
ISBN | Citations | PageRank |
978-1-4799-8687-3 | 2 | 0.37 |
References | Authors | |
12 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yang Mi | 1 | 67 | 16.04 |
| Lihang Liu | 2 | 6 | 0.76 |
| Weiyao Lin | 3 | 732 | 68.05 |
| Weiyue Wang | 4 | 57 | 3.55 |