In this paper, a novel approach to abnormal event detection in crowded scenes is presented
based on a new low-rank and compact coefficient dictionary learning (LRCCDL) algorithm …

Occurrence of high imbalance in real-world domains is a direct result of rarity of interesting
events, which results in skewed datasets. Without dataset rebalancing, the learning …

Occasions such as stalled vehicles or crashes led by abnormal trajectories should be
instantly identified and then dealt with quickly by the city traffic management system for the …

Abnormal events detection plays an important role in the video surveillance, which is a
challenging subject in the intelligent detection. In this paper, based on a novel motion …

We present an approach where a robot patrols a fixed path through an environment,
autonomously locating suspicious or anomalous objects. To learn, the robot patrols this …

In this paper, we propose an algorithm of anomaly detection in crowded scenes by using
sparse representation over the normal bases. First, the histogram of maximal optical flow …

Automatic audio event recognition plays a pivotal role in making human robot interaction
more closer and has a wide applicability in industrial automation, control and surveillance …

Depending on the specific scene in consideration, the abnormal event detection can be
classified into those in crowded scenes and those in uncrowded scenes. Generally, crowd …

Our objective is to count objects using a single frame from a surveillance camera. We focus
on the area where individual object detectors fail, mostly due to clutter, occlusion, or …

Features play a vital role in human action recognition (HAR), as they encapsulate the
underlying dynamics of the action. We propose the features (frequencygrams) based on …