People Detection Enrichment for Abnormal Human Activity Detection

A vibrant branch of research in computer vision that has attracted a lot of attention for decades is the human activity understanding from video. A means for accurately locating humans in image or a video is a prerequisite to the process of understanding human activities or action. This work’s focus is on investigating the use of people detectors for video surveillance in Financial Banks premises so that it can eventually be used for abnormal human activity detection. An integrated framework which is made up of histogram of oriented gradient descriptors and Haar integral features is proposed thus, it is a union of Full body detector and Upper body detector. The proposed framework gives an improvement over the state of the art when applied as a case study to bank security. The technique obtained an F-score of 65.83 and precision of 73.83 and recall of 59.40 percentage points.