Pose-based anomaly detection is a video-analysis technique for detecting anomalous
events or behaviors by examining human pose extracted from the video frames. Human …

Multimedia anomaly datasets play a crucial role in automated surveillance. They have a
wide range of applications expanding from outlier objects/situation detection to the detection …

In machine learning (ML), a widespread adage is that the area under the precision-recall
curve (AUPRC) is a superior metric for model comparison to the area under the receiver …

Abstract Video Anomaly Detection (VAD) identifies unusual activities in video streams a key
technology with broad applications ranging from surveillance to healthcare. Tackling VAD in …

Vehicle Trajectory datasets that provide multiple point-of-views (POVs) can be valuable for
various traffic safety and management applications. Despite the abundance of trajectory …

Abstract Video Anomaly Detection (VAD) represents a challenging and prominent research
task within computer vision. In recent years, Pose-based Video Anomaly Detection (PAD) …

Detecting and tracking objects in image sequences is paramount for any video analytic.
While object detectors have become increasingly robust, motion estimates based on the …

Video anomaly detection is a significant problem in computer vision that aims to detect
unusual or abnormal behaviors in video data that can be used to enhance public safety …

We present a new traffic light object detection dataset of over 4,000 images labeled from
dashcam video in Charlotte, NC. The dataset captures challenging weather and lighting …

This dissertation presents the systematic design and development of datasets, algorithms,
and an AI pipeline specifically curated for real-time trajectory prediction and anomaly …