Please use this identifier to cite or link to this item: https://elibrary.khec.edu.np:8080/handle/123456789/674
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dc.contributor.advisorEr. Milan Chikanbanjar-
dc.contributor.authorNista Shakya (750320)-
dc.contributor.authorPrashamsa Bakhrel (750323)-
dc.contributor.authorPuskar Adhikari (750324)-
dc.contributor.authorRamjanam Sharma (750327)-
dc.date.accessioned2023-09-20T12:13:13Z-
dc.date.available2023-09-20T12:13:13Z-
dc.date.issued2023-08-
dc.identifier.urihttps://elibrary.khec.edu.np/handle/123456789/674-
dc.description.abstractReal-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.en_US
dc.language.isoenen_US
dc.subjectCNN, OpenCV, Canvas, Image Processing, Object Tracking, Transfer Learning iiien_US
dc.titleREAL-TIME OBJECT TRACKING AND SHAPE RECOGNITION USING AIR CANVASen_US
dc.typeTechnical Reporten_US
local.college.nameKhwopa Engineering College-
local.degree.departmentDepartment of Computer-
local.degree.nameBE Computer-
local.degree.levelBachelor's Degree-
local.item.accessionnumberD.1369-
Appears in Collections:Computer Report

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