Deep Learning Technique to Detect Object For Visually Impaired People Using YOLO V3 Framework Mechanism

Abstract

In this project, we recommended a technique called the multi-view object tracking (MVOT) system to resolve the multiple cameras monitor an area from different angles. Videos recorded by the cameras contain complementary information and fusing the knowledge embedded in the videos facilitates the development of a robust and accurate system. Those task of cameras that have different settings, we propose a correspondence Yolo V3 algorithm that maps each segmented group of objects in one view to the corresponding group in another view. We call these corresponding groups matched blob clusters, each of which enables knowledge to be shared between cameras. It follows that we present a two-pass regression framework for multi-view objects.