Surveillance Video Synopsis in GIS
Abstract
:1. Introduction
2. Related Work
3. Surveillance Video Synopsis in GIS
3.1. Extraction and Clustering of Moving Objects
3.1.1. Extraction of Moving Objects
3.1.2. Georeferencing of Moving Object Trajectory
3.1.3. Clustering of Moving Object Trajectories
3.2. Video Synopsis in Virtual Scene
3.2.1. Virtual Field of Vision Generation
3.2.2. Trajectory Fitting Centerline Generation
3.2.3. Expression of Video Moving Object
4. Experimental Results
4.1. Clustering of Moving Object Trajectories
4.2. Visualization of Surveillance Video Synopsis in GIS
- (1)
- On the basis of georeferencing, the moving objects can be classified according to their geographical directions of the trajectory, which cannot be accurately carried out in image space.
- (2)
- There are definite display intervals and timing structural relationship between the moving objects, which avoids the crowding of the video moving objects.
- (3)
- Objects’ moving trajectories can be directly viewed and analyzed along with other geospatial targets in the geographic scene.
4.3. Evaluation of the Timing Compression Rate
4.4. Evaluation of the Accuracy of Moving Object Retrieval
5. Conclusions and Discussion
- (1)
- This study proposed an approach for video synopsis in GIS by extensively applying the model to the integration of video moving objects and GIS.
- (2)
- The proposed approach improves video browsing efficiency while integrating the expression of video and geospatial information.
- (3)
- This work describes the general process and technical details of video synopsis in GIS, discusses the characteristics of the moving object expression model, and evaluates the timing compression rate and moving object retrieval accuracy in the realization of video synopsis.
Acknowledgments
Author Contributions
Conflicts of Interest
References
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ODSR | 0 | 1 | |
---|---|---|---|
CDSR | |||
0 | |||
1 |
CDSR | ODSR = 0 | ODSR = 1 |
---|---|---|
0 | ||
1 |
ODSR | ODSR = 0 | ODSR = 1 = 5 | ODSR = 1 = 10 | ODSR = 1 = 20 | ODSR = 1 = 30 |
---|---|---|---|---|---|
0 | 19.53% | 19.53% | 6.61% | 8.23% | 11.46% |
1 | 11.45% | 3.00% | 4.05% | 6.17% | 8.28% |
β | True Positive | True Negative | False Positive |
---|---|---|---|
0.7 | 95.2% | 4.8% | 0 |
0.75 | 98.4% | 1.6% | 0 |
0.8 | 96.8% | 1.6% | 1.6% |
0.85 | 96.8% | 1.6% | 1.6% |
0.9 | 98.4% | 0 | 1.6% |
0.95 | 98.4% | 0 | 1.6% |
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Xie, Y.; Wang, M.; Liu, X.; Wu, Y. Surveillance Video Synopsis in GIS. ISPRS Int. J. Geo-Inf. 2017, 6, 333. https://doi.org/10.3390/ijgi6110333
Xie Y, Wang M, Liu X, Wu Y. Surveillance Video Synopsis in GIS. ISPRS International Journal of Geo-Information. 2017; 6(11):333. https://doi.org/10.3390/ijgi6110333
Chicago/Turabian StyleXie, Yujia, Meizhen Wang, Xuejun Liu, and Yiguang Wu. 2017. "Surveillance Video Synopsis in GIS" ISPRS International Journal of Geo-Information 6, no. 11: 333. https://doi.org/10.3390/ijgi6110333