Vision-based human action and activity recognition has an increasing importance among
the computer vision community with applications to visual surveillance, video retrieval and …

As surveillance becomes ubiquitous, the amount of data to be processed grows along with
the demand for manpower to interpret the data. A key goal of surveillance is to detect …

Abstract We present the Multiview Extended Video with Activities (MEVA) dataset, a new and
very-large-scale dataset for human activity recognition. Existing security datasets either …

This paper presents an approach for detecting suspicious events in videos by using only the
video itself as the training samples for valid behaviors. These salient events are obtained in …

A robust and efficient anomaly detection technique is proposed, capable of dealing with
crowded scenes where traditional tracking based approaches tend to fail. Initial foreground …

Privacy protection is a growing concern in the digital era, with machine vision techniques
widely used throughout public and private settings. Existing methods address this growing …

In this paper we propose an approach for anomaly detection and localization, in video
surveillance applications, based on spatio-temporal features that capture scene dynamic …

Visual surveillance systems have recently captured the attention of the research community.
Most of the proposed surveillance systems deal with stationary cameras. Nevertheless …

The prevalence of violence in daily life poses significant threats to individuals' physical and
mental well-being. Using surveillance cameras in public spaces has proven effective in …

Abstract Human Motion Analysis (HMA) is currently one of the most popularly active
research domains as such significant research interests are motivated by a number of real …