X. Zhu

TIme Square Intersection (TISI) Dataset (ICCV'13, IJCV'16)

Example frames.

Download
Including image sequences in jpeg format, non-visual weather and traffic speed data. To facilitate downloading this huge video dataset, you may want to download and install the Baidu cloud bulter.

Details

The TIme Square Intersection (TISI) dataset was collected from a publicly accessible webcam for high-level event based video synopsis research. This dataset can be exploited for other computer vision problems, such as video classification or tag annotation.

Image sequences (jpeg format): organised in multiple folders named with the record time (GMT time zone). In each folder 1000 frames are contained. (Note that there is a gap of 5 hours between the New York's time (UTC-05:00) and GMT time)

Weather data (xml format): the weather condition description of the Time Square drawn from the WorldWeatherOnline website, including temperature, weather type, wind speed, wind direction, precipitation, humidity, visibility, pressure, and cloud cover et al. The weather data files named `weather_matched.xml' are distributed in individual folders.

Traffic speed data (jpeg format): the traffic condition description of the Time Square drawn from the Google Maps. Totally four levels of traffic speed are involved: very slow, slow, moderate, and fast. The traffic speed data files named `traffic_condition.jpg' are distributed in individual folders.

Stream length: a total of 2501 folders, each containing 1000 image frames
Frame size: 550x960
Frame rate: ~10 Hz

The dataset is intended for research purposes only and as such cannot be used commercially. Please cite the following publication when this dataset is used in any academic and research reports.

References

  1. Learning from Multiple Sources for Video Summarisation
    X. Zhu, C.C. Loy and S. Gong
    International Journal of Computer Vision, Vol. 117, No. 3, pp. 247-268, May 2016 (IJCV)
    [ PDF ] [ Project Page ]
  2. Video Synopsis by Heterogeneous Multi-Source Correlation
    X. Zhu, C.C. Loy and S. Gong
    In Proc. IEEE International Conference on Computer Vision, Sydney, Australia, December 2013 (ICCV)
    [ PDF ] [ Poster ] [ Project Page ]