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Reseach Article

Smart Trolley Follower using Vision based Technique

Published on June 2016 by Seema Udgirkar, Monish Lalchandani, Rohit Bhonsle, Adityatulpule, Swapnil Satpute
National Conference on Advances in Computing, Communication and Networking
Foundation of Computer Science USA
ACCNET2016 - Number 7
June 2016
Authors: Seema Udgirkar, Monish Lalchandani, Rohit Bhonsle, Adityatulpule, Swapnil Satpute
6ec24254-7e8d-4e11-a662-c5943a27b7a6

Seema Udgirkar, Monish Lalchandani, Rohit Bhonsle, Adityatulpule, Swapnil Satpute . Smart Trolley Follower using Vision based Technique. National Conference on Advances in Computing, Communication and Networking. ACCNET2016, 7 (June 2016), 8-10.

@article{
author = { Seema Udgirkar, Monish Lalchandani, Rohit Bhonsle, Adityatulpule, Swapnil Satpute },
title = { Smart Trolley Follower using Vision based Technique },
journal = { National Conference on Advances in Computing, Communication and Networking },
issue_date = { June 2016 },
volume = { ACCNET2016 },
number = { 7 },
month = { June },
year = { 2016 },
issn = 0975-8887,
pages = { 8-10 },
numpages = 3,
url = { /proceedings/accnet2016/number7/25011-2306/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advances in Computing, Communication and Networking
%A Seema Udgirkar
%A Monish Lalchandani
%A Rohit Bhonsle
%A Adityatulpule
%A Swapnil Satpute
%T Smart Trolley Follower using Vision based Technique
%J National Conference on Advances in Computing, Communication and Networking
%@ 0975-8887
%V ACCNET2016
%N 7
%P 8-10
%D 2016
%I International Journal of Computer Applications
Abstract

This paper introduces a vision-based object tracking robot which is driven by wheels and controlled by a computer along with software. The objective of this paper is to design a robot which is automatically controlled by computer to track and follow a colored object. Emphasis is given on precision vision based robotic applications. Image acquisition by the robot is achieved by ANDROID based camera, then it is sent to image processing software for further processing. The overall paper describes a visual sensor system used in the field of robotics for identification and tracking of the object.

References
  1. . J. W. Davis and A. F. Bobick. The representation andrecognition of human movement using temporal templates. InCVPR, pages 928–934, Puerto-Rico, June 1997. IEEE.
  2. . Y. Rosenberg and M. Werman– Real- Time Object tracking from a Moving Video Camera: A software approach on PC - Applications of Computer Vision, 1998. WACV '98. Proceedings
  3. . Detection of moving objects in a video stream acquired by an airborne platform, Detecting and Tracking Moving Objects for Video Surveillance. By Isaac Cohen, Gerard Medioni, 1999.
  4. . Laser-based person-tracking method And two different approaches to person following: direction-following and path- following, Natural Person-Following Behavior for Social Robots, By Rachel Gockley, Jodi Forlizzi, Reid Simmons,2007.
  5. . Concepts of histogram matching and absolute frame subtraction to implement a robust automated object tracking system, Real time object detection and tracking: Histogram matching and Kalman filter approach, By Mehta M,Goyal C, Srivastava,2010.
  6. . Structure from motion (SfM) is the extension of classical SfM to dynamic scenes with multiple rigidly moving objects, Multi-body structure-from- motion in practice. By K. E. Ozden, K. Schindler, and L. Van Gool, 2010.
  7. . R. Gockley and M. Matari´c. Encouraging physical therapy compliance with a hands-off mobile robot. In Proceedings of Human-Robot Interaction, Mar2006.
  8. . E. Prassler, D. Bank, and B. Kluge. Key technologies in robot assistants: Motion coordination between a human and a mobile robot. Transactions on Control, Automation and Systems Engineering, 4(1):56–61, Mar. 2002.
Index Terms

Computer Science
Information Sciences

Keywords

Image Processing Android Atmega- 32(avr Family Blobbing)