We propose an online multi-target tracker that exploits both high-and low-confidence target
detections in a Probability Hypothesis Density Particle Filter framework. High-confidence …

The paper presents a comprehensive overview of intelligent video analytics and human
action recognition methods. The article provides an overview of the current state of …

Most existing tracking approaches are based on either the tracking by detection framework
or the tracking by matching framework. The former needs to learn a discriminative classifier …

Biological systems are frequently categorized as complex systems due to their capabilities of
generating spatio-temporal structures from apparent random decisions. In spite of research …

Tracking and action-recognition algorithms are currently widely used in video surveillance,
monitoring urban activities and in many other areas. Their development highly relies on …

Inverse synthetic aperture radar (ISAR) object detection is one of the most challenging
problems in computer vision, and most existing ISAR object detection algorithms are …

This work applies sparse representations and nonlinear image processing to two inverse
imaging problems. The first problem involves image restoration, where the aim is to …

Identifying underlying governing equations and relevant information from high-dimensional
observable data has always been a challenge in physical sciences. With the recent …

Multiple-object tracking constitutes a major step in several computer vision applications,
such as surveillance, advanced driver assistance systems, and automatic traffic monitoring …

Metrics on the space of sets of trajectories are important for scientists in the field of computer
vision, machine learning, robotics, and general artificial intelligence. However, existing …