Computer Vision (CV) based surveillance in crowded scenes is one of the most significant
and promising topics due to the increase of people gatherings in public places where the …

In this paper, we propose a hybrid agent method to detect abnormal behaviors in a crowded
scene. In real-life situations, abnormal behavior occurs by violent movement which is …

Highlight detection is a fundamental step in semantics based video retrieval and
personalized sports video browsing. In this paper, an effective hidden Markov models …

In this paper, we propose a detection algorithm based on people counting for two special
kinds of abnormal crowd behavior, gathering and dispersing. We use an efficient foreground …

This paper presents a novel approach for unexpected behavior recognition in image
sequences with attention to high density crowd scenes. Due to occlusions, object-tracking in …

We propose a method to detect abnormal crowd behavior using integrated multiple behavior
models. Traditional abnormal detection methods are based only on personal behavior …

In this paper, an approach to semantic video analysis that is based on the statistical
processing and representation of the motion signal is presented. Overall, the examined …

In view of the traditional support vector machine (SVM) learning algorithm for widespread
learning parameters is not easy determined in the process of video key frame extraction, the …

Detect highlight event is an important step for semantic-based video retrieval. Hidden
conditional random field (HCRF) is a discriminative model, which is effective in fusing …

In view of the traditional support vector machine (SVM) learning algorithm's learning
parameters are not easily determined in the process of video key frame extraction and the …