These are demo videos for the TCSVT journal paper, “Counting People Crossing a Line using Integer Programming and Local Features.” The result video is available in “.mov” format. The datasets are available here.
1. Results for USCD Dataset
video ucsd.mov – counting results for the UCSD pedestrian dataset (2000 frames), with 1200 frames for testing and 800 frames for training. An example video frame is shown below:
![](/static/images/linecount/UCSD.png)
[mov (13.1 MB)]
Instantaneous count results
These are results of instantaneous count estimationon for the 2000 frames with temporal slice image.
The system was trained on 800 frames.
![](/static/images/linecount/results/crowd_density_ucsd.png)
Cumulative count resuls
These are the plots of the cumulative counts over time on the testing set (1200 frames).
right![]() |
left![]() |
2. Results for LHI Dataset
video 3-3 LHI.mov – counting results for the video 3-3 (2000 frames) of LHI crowd dataset, with 1200 frames for testing and 800 frames for training. An example video frame is shown below:
![](/static/images/linecount/LHI_3-3.png)
[mov (7.3 MB)]
Instantaneous count results
These are results of instantaneous count estimation on for the 2000 frames with temporal slice image.
The system was trained on 800 frames.
![](/static/images/linecount/results/crowd_density_LHI.png)
Cumulative count results
These are the plots of the cumulative counts over time on the testing set (1200 frames).
right![]() |
3. Results for Grand Central Dataset
The video is collected from the inside of the Grand Central railway station in New York. The yellow lines are the Lines-of-interest for our line counting algorithm. One example of the video is shown below:
Instantaneous count results
L1 frame 1 to 2000
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Cumulative count results
The cumulative counting results for L1 to L8 on Grand Central datasets over testing set (7000 frames)