ahmed-nady/real-time-abnormal-event-detection-in-crowded-scenes

This project is based on STACOG descriptor to detect anomalous event in real-time

Real-Time-Abnormal-Event-Detection-in-Crowded-Scenes

This project is based on STACOG descriptor [1] to detect anomalous crowd event in real-time.

The underlying assumption of the method presented here is that the abnormal event differs from normal ones in their space-time motion pattern. So, STACOG features that considered as spatio-temporal representation is extracted from video sequences. We then perform K-medoids clustering using training features. During the test phase, the anomaly score of each frame is determined from distances between frame-based feature STACOG and center of the clusters.

The proposed anomaly detection method was tested on benchmark dataset: UMN dataset, PETS2009. Experiments show that the proposed method achieves comparable results with the state-of-the-art methods in terms of accuracy while requiring a low computational cost than alternative approaches

References [1] T. Kobayashi and N. Otsu, “Motion recognition using local auto-correlation of space–time gradients,” Pattern Recognition Letters, vol. 33, no. 9, pp. 1188–1195, 2012.

Citation Details

Please cite the following paper when using this source code: A. Nady, A. Atia, A. E. Aboutabl, “Real-Time Abnormal Event Detection in CrowdedScenes”, Journal of Theoretical and Applied Information Technology.96(18):6064-6075, September2018. https://www.researchgate.net/publication/327972246_REAL-TIME_ABNORMAL_EVENT_DETECTION_IN_CROWDED_SCENES

real-time-abnormal-event-detection-in-crowded-scenes's Issues

Dateset is not here

Hello, I read your code,while I can not understand the the path in your code ,could you give the dateset in your project,such as test and train ,I have the dataset you have mentioned.But ,I do not divide it into details.

If you could upload the dataset you mentioned ,Thanks so much.