Multi-object tracking (MOT) has been notoriously difficult to evaluate. Previous metrics
overemphasize the importance of either detection or association. To address this, we …

We present a novel multifeature video object trajectory clustering algorithm that estimates
common patterns of behaviors and isolates outliers. The proposed algorithm is based on …

Convolutional neural networks are a popular choice for current object detection and
classification systems. Their performance improves constantly but for effective training, large …

Evaluation of tracking algorithms in the absence of ground truth is a challenging problem.
There exist a variety of approaches for this problem, ranging from formal model validation …

In low-resolution wide-area aerial imagery, object detection algorithms are categorized as
feature extraction and machine learning approaches, where the former often requires a post …

Unlike terrestrial networks, the received signal strength in maritime wireless networks are
subjected to perturbations due to the sea movement. Surface motions at sea cause …

This paper presents two tracking approaches from Sarnoff Corporation to detect moving
vehicles and person in the videos taken from aerial platform or plane. In the first approach …

Multiple object tracking is a fundamental subsystem of many higher level applications such
as traffic monitoring, people counting, robotic vision and many more. This paper explains in …

Performance analysis of object detection combined with post-processing schemes are
challenging especially that the spatial resolution of images is low in wide-area aerial …

We present an object detection and tracking algorithm that addresses the problem of
multiple simultaneous targets tracking in real-world surveillance scenarios. The algorithm is …