Table 8 Summary of different techniques in video analysis
From: Intelligent video surveillance: a review through deep learning techniques for crowd analysis
Title | Method | Tool | Data set |
|---|---|---|---|
Scenario-based query processing for video-surveillance archives [95] | Query processing system and inverted tracking | VSQL | PETS 2006 and PETS 2007 |
Activity retrieval in large surveillance videos [96] | Dynamic matching algorithm | Query creation GUI | Pets, Mit traffic |
Integrated video object tracking with applications in trajectory-based event detection [97] | Adaptive particle sampling and Kalman filtering | Not mentioned | PETS 2001 test dataset1, camera 1 |
Evidential event inference in transport video surveillance [98] | Using spatio-temporal correlations for reasoning | Jones and Viola face detector | Own data set |
Abnormal event detection based on analysis of movement information of video sequence [99] | Optical flow and Hidden Markov model | Not mentioned | UMN, PETS |
Anomalous entities detection and localization in pedestrian flows [100] | Gaussian kernel based feature integration and R-CRF model based classification | Not mentioned | UCSD, UMN, UCD |
Snatch theft detection in unconstrained surveillance videos using action attribute modelling [101] | A large GMM called universal attribute model | Â | Own Dataset Snatch 1.0 |
ArchCam: real time expert system for suspicious behaviour detection in ATM site [102] | Image processing technique | NVIDIA Tegra TX1 SoC 340 with quad core ARM processor and 256 cores GPU | Videos under a mock ATM setup |