Please use this identifier to cite or link to this item:
https://elibrary.khec.edu.np:8080/handle/123456789/674
Title: | REAL-TIME OBJECT TRACKING AND SHAPE RECOGNITION USING AIR CANVAS |
Authors: | Nista Shakya (750320) Prashamsa Bakhrel (750323) Puskar Adhikari (750324) Ramjanam Sharma (750327) |
Advisor: | Er. Milan Chikanbanjar |
Keywords: | CNN, OpenCV, Canvas, Image Processing, Object Tracking, Transfer Learning iii |
Issue Date: | Aug-2023 |
College Name: | Khwopa Engineering College |
Level: | Bachelor's Degree |
Degree: | BE Computer |
Department Name: | Department of Computer |
Abstract: | Real-time Object Tracking and Shape Recognition Using Air Canvas is an innovative application that offers real-time drawing capabilities by detecting a green object in the camera feed. Built on OpenCV, the application tracks the movement of the green object in the air and translates it into drawing actions on the screen. The application employs a Convolutional Neural Network (CNN) model to accurately recognize and classify the shapes drawn by the user. With its seamless integration of computer vision techniques and deep learning algorithms, this application provides an intuitive and interactive drawing experience, making it a unique tool for creative exploration. |
URI: | https://elibrary.khec.edu.np/handle/123456789/674 |
Appears in Collections: | Computer Report |
Files in This Item:
File | Description | Size | Format | |
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RTOS-Air Canvas - final_report.pdf Restricted Access | 4.43 MB | Adobe PDF | View/Open Request a copy |
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