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Different Techniques of Object Detection and Tracking: In Video Monitoring System

EasyChair Preprint 3491

9 pagesDate: May 27, 2020

Abstract

The paper includes the various methods which are related to object detection and tracking in live video surveillance to detect the object like the face or can be used to detect the people, cars in a security camera. These days we can easily find that people are following social distancing due to COVID -19. This paper point towards the various methods of detecting the object (classification) and tracking (GMM tracking). This paper points toward the detection of movable objects in the live video monitoring then tracking will track the moving object. Detecting a moving object is really a very big task and it the origin of the method. Object detection is really difficult to implement which depends upon the shape size and color of the object. In this paper, we will study the background subtraction using the pixel-based method, optical flow method, color-based method gradient-based method and frame differencing. We will also study tracking methods like kernel-based method silhouette-based method, and point-based methods.

Keyphrases: Foreground detection method, Temporal Frame Differencing, object detection, object tracking, point-based methods

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:3491,
  author    = {Saurabh Patel and K Sampath Kumar},
  title     = {Different Techniques of Object Detection and Tracking: In Video Monitoring System},
  howpublished = {EasyChair Preprint 3491},
  year      = {EasyChair, 2020}}
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