Name
Abstract | ||
|---|---|---|
Spatio-temporal activity maps have been used to visualize where activity occurs over time, as captured by a camera, and have typically been displayed as heat maps. We extend this work in two ways. 1) Multiple maps from many cameras in a network are geometrically translated to create a unified, wide-area map whose viewing angle and relative feature values are consistent to all cameras. 2) Activity features are extended beyond density, to include direction, bi-direction, and dwell time. Experimental results are shown to illustrate the types of transformations and corrections needed for unified multi-camera display, and their accuracy. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICPR.2014.785 | Pattern Recognition |
Keywords | DocType | ISSN |
feature extraction,image motion analysis,spatiotemporal phenomena,video cameras,video signal processing,activity features,feature values,heat maps,motion analysis,multicamera networks,spatiotemporal activity maps,unified multicamera display,unified wide-area activity map,video analysis,activity maps,heat maps,motion analysis,video analysis | Conference | 1051-4651 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lawrence O'Gorman | 1 | 182 | 11.81 |
| Dorel Livescu | 2 | 1 | 0.35 |
| Guang Yang | 3 | 1 | 0.35 |