Object detection with a learned classifier has been applied successfully to difficult tasks such
as detecting faces and pedestrians. Systems using this approach usually learn the classifier …

Speedy abnormal event detection meets the growing demand to process an enormous
number of surveillance videos. Based on inherent redundancy of video structures, we …

This article compares the performance of target detectors based on adaptive background
differencing on public benchmark data. Five state of the art methods are described. The …

Surveillance cameras are inexpensive and everywhere these days but the manpower
required to monitor and analyze them is expensive. Consequently the videos from these …

In this paper, we propose a trajectory clustering algorithm suited for video surveillance
systems. Trajectories are clustered on-line, as the data are collected, and clusters are …

This paper proposes a novel method for detecting foreground objects in nonstationary
complex environments containing moving background objects. We derive a Bayes decision …

Background In modern intelligent video surveillance systems, automatic anomaly detection
through computer vision analytics plays a pivotal role which not only significantly increases …

In this paper we propose a robust approach to detect moving objects for video surveillance
applications. We demonstrate that a jointly use of frame by frame difference with a …

Video anomaly detection plays a critical role for intelligent video surveillance. We present an
abnormal video event detection system that considers both spatial and temporal contexts. To …

This paper describes a new real-time approach for detecting changes in grey level image
sequences, which were taken from stationary cameras. This new method combines a …