Warwick-NTU Multi-camera Forecasting (WNMF) database

This page introduces the Warwick-NTU Multi-camera Forecasting dataset (WNMF). If you would like to access the database, please use request access form at the bottom of this page. For code and further details, please see our GitHub repository: https://github.com/olly-styles/Multi-Camera-Trajectory-Forecasting


Dataset contents

The WNMF dataset contains footage of individuals traversing the Nanyang Technological University (NTU) campus. The dataset contains cross-camera tracking information, such that future trajectories of individuals can be anticipated across multiple camera views. The data was collected over a span of 20 days using 15 different CCTV cameras. This was not a controlled collection (i.e., it was collected in real-world conditions).

Raw data statistics:

We release camera entrance and departure videos, pre-computed tracking information and RE-ID features. Faces are blurred using the RetinaFace algorithm [1] to detect faces. Provided are the 4 seconds proceeding a camera departure event and 12 seconds following a camera entrance event, totally 16 seconds for each verified cross-camera match.

Hours of footage


Number of cameras


Collection period

20 days

Time period

8:30am – 7:30pm

Video resolution

1920 by 1080

Frames per second


Cross camera matches


Released data statistics:

Hours of footage


Cross-camera matches after verification


Mean cross-camera RE-IDs per track


How to obtain the dataset:

To download the dataset, please see the request access form at the bottom of this page.

Sample videos

Camera departure example (tracking data shown)

Camera entrance example (tracking data hidden)

Usage for Academic Research

This video dataset is released for academic research only, and is free to researchers from educational or research institutes for non-commercial purposes.


All publications using the WNMF dataset should include the following acknowledgement: “(Portions of) the research in this paper used the WNMF Dataset made available by the SIP Lab at the University of Warwick, United Kingdom, and the ROSE Lab at the Nanyang Technological University, Singapore.”

Any publications that result from using the WNMF dataset should cite the following paper: Olly Styles, Tanaya Guha, Victor Sanchez, Alex C. Kot, “Multi-Camera Trajectory Forecasting: Pedestrian Trajectory Prediction in a Network of Cameras”, IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2020

If interested, please click on the "Request Dataset" hyperlink below for a copy of the Release Agreement. With your acceptance of the agreement, we will then send you the LoginID and password to the dataset.

Request Dataset

*Link to release agreement* https://github.com/olly-styles/Multi-Camera-Trajectory-Forecasting/blob/master/WNMF%20release%20agreement.pdf

*Link to request dataset* https://github.com/olly-styles/Multi-Camera-Trajectory-Forecasting



[1] Deng, J., Guo, J., Zhou, Y., Yu, J., Kotsia, I. and Zafeiriou, S., 2019. Retinaface: Single-stage dense face localisation in the wild. arXiv preprint arXiv:1905.00641.