We propose a principled probabilistic formulation of object saliency as a sampling problem.
This novel formulation allows us to learn, from a large corpus of unlabelled images, which …

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 …

The growing need for information and high-quality video cameras has led to the proliferation
of video based systems that perform tasks such as traffic monitoring, surveillance, etc. A …

One of the most interesting and desired capabilities for automated video behavior analysis is
the identification of rarely occurring and subtle behaviors. This is of practical value because …

Human eyes are highly efficient devices for scanning through a large quantity of low-level
visual sensory data and delivering selective information to one's brain for high-level …

We propose a fully unsupervised method for abnormal activity detection in crowded scenes.
Neither normal nor abnormal training examples are needed before detection. By observing …

Interestingness is said to be the power of attracting or holding one's attention (because
something is unusual or exciting, etc.). We, as humans, have the great capacity to direct our …

We propose a data-driven, hierarchical approach for the analysis of human actions in visual
scenes. In particular, we focus on the task of in-house assisted living. In such scenarios the …

In the last decades, many efforts have been devoted to develop methods for automatic
scene understanding in the context of video surveillance applications. This paper presents a …

To improve the accuracy of the detection of local abnormal behavior, a novel method is here
proposed. The main idea of the proposed method is described as follows: firstly, a video …