In this paper, we propose an approach for surveillance video indexing and retrieval. The
objective of this approach is to answer five main challenges we have met in this domain:(1) …

The goal of this work is to learn and retrieve a sequence of highly correlated patterns using a
Hopfield-type of attractor neural network (ANN) with a small-world connectivity distribution …

While many overview papers have been published for information retrieval in general and
image retrieval in particular, there is a lack of paper in the literature focusing on retrieval for …

Traffic incidents are frequent query targets in a transportation surveillance video database.
Therefore, understanding and retrieving transportation videos based on their semantic …

Detecting and retrieving incidents from traffic surveillance videos is an important research
topic in designing an Intelligent Transportation System (ITS). Most existing video analysis …

This paper presents data modeling and query processing for distributed surveillance
systems. We define a metadata rule to search and manage information for distributed or …

This thesis explores the emergence of spatially localized information in Attractor Neural
Networks with metric connectivity. The spatial information examined is arranged in blocks of …

In this paper, we propose a relevant feedback algorithm based on supervised classification
and unsupervised feature extraction using independent component analysis (ICA). First, we …

The focus of this survey is on spatio-temporal data mining and database retrieval for visual
traffic surveillance systems. In many traffic surveillance applications, such as incident …

Learn and retrieve a sequence of sparse-coded patterns that are highly correlated over time:
Traffic video sequences Correlated sequence of patterns Sparse coding patterns How to …