In this paper we present an instance based machine learning algorithm and system for real-
time object classification and human action recognition which can help to build intelligent …

Video data is highly expressive and has traditionally been very difficult for a machine to
interpret. Querying event patterns from video streams is challenging due to its unstructured …

Automated video surveillance has emerged as a trendy application domain in recent years,
and accessing the semantic content of surveillance video has become a challenging …

Modern video surveillance systems often consist of multiple cameras capturing continuous
videos. However, existing systems do not fully take advantage of shared scene semantics …

In this paper, we propose a novel query language for video indexing and retrieval that (1)
enables to make queries both at the image level and at the semantic level (2) enables the …

Those who are in pursuit of a comfortable life should forget about learning and those who
are in pursuit of learning should forget about comfortable living. Those who are after …

The manual search through the surveillance video archives for a specific object or event is
very timeconsuming and tedious task due to the large volume of video data captured by …

Spatio-temporal saliency detection has gradually gained much attention in various computer
vision applications such as intelligent video advertising and visual tracking. In this paper, we …

Event representation models provide a framework in which we can reason about events so
as to interpret the collective behaviour of objects over time and space domains. Many are …

Massive amounts of videos are generated for entertainment, security, and science, powered
by a growing supply of user-produced video hosting services. Unfortunately, searching for …