Abstract
Real Time Multi-Object Tracking based on Faster RCNN and Improved Deep Appearance Metric
Highlights
MultiObject Tracking (MOT) tracks moving objects with the regular time interval via camera as the input device
In this paper we propose a system to reduce the number of objects being missed from detection in multiple objects using Faster region Convolution neural network (RCNN)
We discovered that ResNet-101 based Faster RCNN is giving better performance
Summary
MOT tracks moving objects with the regular time interval via camera as the input device. In 1998, Zenon Pylyshyn [1] was first developed multi-object tracking. Each detected object is assigned a unique identification number. This identity number retains its association with the object when changing the object’s appearance or object moving and draw the motion trajectories of the object based on the unique identities. Multiobject detection finds the objects under a unique frame and MOT is integrated with the detected objects in the sequence of frames
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