Orthographic Perspective Mappings for Consistent Wide-Area Motion Feature Maps From Multiple Cameras


Spatiotemporal activity maps have been used to visualise where activity occurs over time, and are often displayed as pseudo-color heat maps. Our multi-dimensional activity map includes the following motion options: density, direction, bi-direction, velocity, and dwell. The primary contribution of this paper is to describe a set of mappings that will rework the activity maps captured from the cameras of different views to those from one orthographic perspective. The aim of this can be to be able to view and compare multiple activity maps from different camera views over a good space with consistently comparable data. A second contribution is that the most mappings are based mostly upon statistically learned camera perspectives to attenuate manual camera calibration. We tend to demonstrate mapping results with multiple video knowledge sets and describe applications for visualization and wide-area spatial likelihood estimation.

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