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Ground truth is crucial in the performance evaluation of algorithms. Nevertheless, it is a tedious and time-consuming task to annotate ground truth manually, especially in crowd scenes. In this paper, we propose a novel semi-automatic tool called SAGTA (Semi-automatic Ground Truth Annotation Tool), which can assist researchers to annotate pedestrians easily and quickly in crowd scenes. Firstly, users...
This paper proposes an improved online framework based on Compressive Tracker (CT) for multiple pedestrian tracking in surveillance videos. The CT method proposed by Zhang et al was originally used for single object tracking, and fails to make use of context information during the tracking process. To overcome the crucial drawbacks of CT, our method implements multi-scale tracking and fuse CT with...
Object tracking is an important issue in video surveillance. In this paper, we present a tracking framework based on ORB (Oriented FAST and Rotated BRIEF) feature using temporal-spacial constraint. ORB is a fast binary descriptor which needs low computation cost and has similar matching performance with SIFT or SURF. Firstly, ORB keypoints and their descriptors of the object are calculated on two...
Overwhelming amounts of surveillance video data are increasingly screwed up the pressure on efficient content-based retrieval and other applications. However, semantic gap exists between the low-level visual signal processing and high-level semantic understanding of the video event. In this paper, we propose an ontology-based content archive and retrieval framework for surveillance videos. Different...
In this paper, a novel Cross-Layered Hidden Markov Model (CLHMM) is proposed for high accuracy and low complexity Surveillance Event Recognition (SER). Unlike existing Layered HMM (LHMM) whose inferences are limited in adjacent layers, cross-layer inferences are designed in CLHMM to strengthen reasoning efficiency and reduce computational complexity. One Common Feature Particle Set (CFPS) is also...
Limited by the restriction of bandwidth, it is difficult to meet the high quality and low-time-delay requirements simultaneously for the practical wireless video surveillance systems. In this paper, a dual-stream coding and transporting scheme is proposed to provide one possible solution. In the proposed system, two streams for one surveillance video are generated: one is low-bitrate coded and transported...
Abnormality Detection (AD), being the core part of intelligent surveillance systems, is calling for growing research interest due to its importance in providing higher efficiency and labor saving. In this paper, we propose a novel Bayesian Network (BN) based AD method for smart surveillance in scenes containing large scale viewpoint changes without model-relearning. In the proposed AD scheme, Reasoning...
For intelligent video surveillance application, the problem of ghosts that appears on motion detection may impose adverse impact on target identification. Based on the spatial-temporal correlations at pixels of the contour area of foreground blobs (PCFB), an efficient method for detecting ghost and left objects is proposed in this paper. This method contains three main steps: firstly, the average...
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