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These are demos of the crowd counting system. The video is available in Quicktime format (H.264).
Pedestrian Database (2000 frames with ground truth)This is a demo of the crowd counting system on the pedestrian dataset (2000 frames). The system was trained on 800 frames, and tested on 1200 frames.Crowd Counting Demo An example video frame is shown below. The error indicator summarizes the performance of the system with respect to the groundtruth. The different colors indicate the following: (green dot) the estimate is within one standarddeviation of the groundtruth; (yellow dot) the estimate is within two standarddeviations; (red dot) the estimate is outside 2 standarddeviations. Finally, the frames marked as "training set" were used to train the GP regression model, and the regionofinterest is also highlighted. The video is sped up to twice the normal frame rate. [mov (9.4 MB)] Crowd Count Plot These are plots of the crowd count over time. The gray regions are the twostandarddeviations error bars of the Gaussian process regression (i.e. the confidence of the crowd estimate). Click the image to see a larger version.
Pedestrian Database (1 hour)This is a demo of the crowd counting system on an hourlong pedestrian video. The system was trained on the 2000 frames with groundtruth, and tested on the remaining 50 minutes video. The video is sped up by 2 times, and each clip is about 35 minutes long.Note that this segmentation required no reinitialization at any point, or any other type of manual supervision. The sequences contain a fair variability of traffic density, various outlying events (e.g. bicyclies, skateboarders, or small vehicles, pedestrians changing direction, etc.) and variable environmental conditions (e.g. varying clouds and shadows).
Training Set Video
Test Set Video
Crowd Count Plot This is a plot of the crowd count for all the video. The bars indicate when the system has low confidence in the count estimates (i.e. when the standarddeviation of the Gaussian process is over 3). Click the image for a larger version.

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