Titre : | YOUTUBE DISTRIBUTED VIDEO CONTENT ANALYSIS PLATFORM | Type de document : | projet fin études | Auteurs : | EL MAALOUMI HAITAM, Auteur | Année de publication : | 2018 | Langues : | Anglais (eng) | Catégories : | Internet des Objets et Services Mobiles ( IOSM )
| Mots-clĂ©s : | Video data, Big Data, YouTube, Machine Learning, Analytical Platform | Index. dĂ©cimale : | mast 33/18 | RĂ©sumĂ© : | Videos are considered to be one of the richest sources of information, but because of their complex and unstructured nature, they pose a challenge to big data analysts and eventually remain unexploited. Nowadays, video data constitutes a huge portion of the internet traffic, due to the ever-growing popularity of social media networks and video sharing sites such as YouTube. This project aims to exploit and analyze video data – from YouTube - at a large scale, detecting objects and recognizing faces that appear in the video. Through this project, we want to demonstrate the benefits of combining Big Data and Machine Learning to build an analytical platform. The present document is a proof of concept for the implementation of such a system.
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YOUTUBE DISTRIBUTED VIDEO CONTENT ANALYSIS PLATFORM [projet fin études] / EL MAALOUMI HAITAM, Auteur . - 2018. Langues : Anglais ( eng) Catégories : | Internet des Objets et Services Mobiles ( IOSM )
| Mots-clĂ©s : | Video data, Big Data, YouTube, Machine Learning, Analytical Platform | Index. dĂ©cimale : | mast 33/18 | RĂ©sumĂ© : | Videos are considered to be one of the richest sources of information, but because of their complex and unstructured nature, they pose a challenge to big data analysts and eventually remain unexploited. Nowadays, video data constitutes a huge portion of the internet traffic, due to the ever-growing popularity of social media networks and video sharing sites such as YouTube. This project aims to exploit and analyze video data – from YouTube - at a large scale, detecting objects and recognizing faces that appear in the video. Through this project, we want to demonstrate the benefits of combining Big Data and Machine Learning to build an analytical platform. The present document is a proof of concept for the implementation of such a system.
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