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Home / programming language / Online Matlab Projects / Determination of Age and Gender Based on Features of Human Motion Using AdaBoost Algorithms
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Determination of Age and Gender Based on Features of Human Motion Using AdaBoost Algorithms

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SKU: PROJ8476 Categories: 2018-2019 Projects, Digital Image Processing Projects, Online Matlab Projects Tags: Android Project, Asp.Net Project, C# Project, Computer Engineering Final Year Projects, Computer Science Final Year Projects, Electronics Projects Engineering Students Final Year, Engineering Student Project Ideas, Final Semester Projects, Final Year Project Center, Final Year Projects, ieee ECE Projects, ieee EEE Projects, ieee Final Year Projects, IEEE Projects, ieee Projects Networking, Image Processing Projects, J2EE Project, Java Project, Matlab Project, PHP Project, Students Projects
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Determination of Age and Gender Based on Features of Human
Motion Using AdaBoost Algorithms

Abstract-Automated human identification by their walking behavior is a challenge attracting much interest among machine vision researchers. However, practical systems for such identification remain to be developed. In this study, a machine learning approach to understand human behavior based on motion imagery was proposed as the basis for developing pedestrian safety information systems. At the front end, image and video processing was performed to separate foreground from background images. Shape-width was then analyzed using 2D discrete wavelet transformation and 2D fast Fourier transformation to extract human motion features. Finally, an adaptive boosting (AdaBoost) algorithm was performed to classify human gender and age into its class based on spatiotemporal information. The results demonstrated the capability of the proposed systems to
classify gender and age highly accurately.

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