Edge-based Crowd Detection from Single Image Datasets

This paper describes the design of a crowd-based facial detection and recognition system using only optical features, allowing for robustness in tracking characterizations with applications in security and data extraction. Implementation is divided into three parts: packing information regarding a given image into edge pixels, segmentation into object groups, and circular segmentation. Detection is achieved by filtering the circles and characterizing those with features similar to that of a normal face. Preliminary facial recognition is described by matching feature vectors to each ”facial region” and matching over subsequence image frames. Algorithms were implemented in MATLAB and testing was performed with a low-resolution video camera. Through a number of trials, results show good detection and tracking abilities given small to medium crowd sizes. Several limitations will be addressed. Keywords—Computer Vision, Sobel, Facial Detection, Ellipses