Subway dataset anomaly detection. )， or UCF-Crime (real-world anomaly).

Subway dataset anomaly detection. This paper aims to help move this research effort forward by introducing a large and varied new dataset called Street Scene, as well as two new evaluation criteria that provide a better estimate of how an algorithm will Aug 3, 2025 · 在计算机视觉的大研究领域内，有一个小方向叫做异常检测（Anomaly Detection），也叫做新颖性检测。 在该方向下有以下的 数据集 作为大家所提出的新的研究方法的检测精度的测试。UCSD, Subway dataset , Avenue Dataset, shanghaiTech, UCF-Crime UCSD异常检测数据集：视频–>图片 May 28, 2023 · Additionally, to overcome the aforementioned issues, this research will generate a new crowd anomaly video dataset based on the Hajj pilgrimage scenario. In this work, an abnormal event detection method was proposed to detect the occurrence of an anomaly automatically by using generative adversarial network (GAN) and streak flow acceleration. Sep 22, 2023 · Automatic detection and interpretation of abnormal events have become crucial tasks in large-scale video surveillance systems. Generally, anomaly detection in recent researches are based on the datasets from pedestrian (likes UCSD, Avenue, ShanghaiTech, etc. On the proposed dataset, the UCSD Ped2, Subway Entry, and Subway Exit datasets, the proposed FCNN-based technique obtained ultimate accuracy of 100%, 90%, 95%, and 89%, respectively. Mar 1, 2024 · Subway-Entry and Subway-Exit dataset: The subway dataset consists of two lengthy videos of two distinct indoor environments: a subway entry and an exit. txt says: In order to obtain the video, please contact Amit Adam (amitadam@yahoo. I'm sending a email to Prof. In other words, the events which deviate from the learned model are considered as abnormal. Feb 9, 2024 · Inspired by this, this paper formulates the abnormal passenger flows into different categories in terms of the characteristics and periodical trends, and proposes a two-step abnormal detection scheme to identify the anomalies and their type, and locate abnormal positions. eh zgtxx eb 6z 3aeaku ciyh0 xe qx1kz ipqxv l2jv