WebJul 27, 2024 · The growing interest in deep learning approaches to video surveillance raises concerns about the accuracy and efficiency of neural networks. However, fast and … The size of \mathbf{S}_i \in {{\mathbb {R}}}^{p\times s} controls the sparsity level. We experimentally set s = 0.1 \times p where p is the data dimension. \lambda in Eq. (2) is the error upper bound, set to 0.04 in experiments. Given the input video, we resize each frame to 3 scales with 20 \times 20, 30 \times 40, and 120 … See more Surveillance videos consist of many redundant patterns. For example, in subway exit, people generally move in similar directions. These patterns share information coded in our sparse combinations. To … See more We conduct quantitative comparison with previous methods on the Subway dataset (Adam et al. 2008). The videos are 2 h long in total, … See more We construct a new avenue dataset for evaluation. In comparison to our conference version, we extend the avenue dataset from 23 videos to 37 videos. The videos are captured in a campus with 30652 (15328 for … See more The UCSD Ped1 dataset (Mahadevan et al. 2010) provides 34 short clips for training, and another 36 clips for testing. All testing clips have frame-level ground truth labels, and 10 … See more
Sensor Fusion Approach for Multiple Human Motion Detection for …
WebAbnormal Situation Management and Early Event Detection Manufacturers recognize the value of an integrated abnormal situation management® program as crucial to … WebA very fast approach for abnormal event detection proposed by Lu et al uses spatio-temporal gradient forsparse learning[14]. They used a sparse combination learning instead of sparse dictionary learning and this improved the detection speed consider-ably. Toobtainthespatio-temporalgradient,thevideoisdi- give earth a hand
(PDF) Fast Anomaly Detection in Traffic Surveillance …
WebMar 20, 2016 · Fast abnormal events detection in video is important for intelligent analysis of video. This paper proposes a fast anomaly detection algorithm based on sparse optical flow. We improve the ... WebNov 16, 2024 · Detecting abnormal events in video is commonly framed as a one-class classification task, where training videos contain only normal events, while test videos … WebAug 1, 2024 · Fast Abnormal Event Detection Cewu Lu 1 · Jianping Shi 2 · Weiming Wang 3 · Jiaya Jia 4 Received: 22 February 2016 / Accepted: … give each ionic compound an appropriate name