Advertisement embedding for online videos

Nowadays, most existing online video players and websites provide search function. However, the search function can only be realized by key word matching. Often, a user want to search for videos that contain a certain object which is hard to describe in key words. In this situation, a search method...

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Bibliographic Details
Main Author: Han, Wei.
Other Authors: Yuan Junsong
Format: Final Year Project (FYP)
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/54506
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author Han, Wei.
author2 Yuan Junsong
author_facet Yuan Junsong
Han, Wei.
author_sort Han, Wei.
collection NTU
description Nowadays, most existing online video players and websites provide search function. However, the search function can only be realized by key word matching. Often, a user want to search for videos that contain a certain object which is hard to describe in key words. In this situation, a search method using a query image as a key is needed. The method to find and locate a target object in a large collection of images or videos is called Visual Object Search. Visual Object Search can also be used for embedded online videos advertisement. It enables online video websites to efficiently and accurately embed advertisements of a commercial product to corresponding video frames that contain the commercial product. In this project, a video search algorithm was developed based on a Visual Object Search method using Randomized Visual Phrase via Random Partition, which is proposed and developed by a research team lead by Professor Yuan Junsong from NTU. A Windows 8 Store App was built implementing the video search algorithm. The App enables users to search and locate a query image in real time in a large collection of videos. The search result of the App is accurate enough for practical application. In addition, a video advertisement interface was also designed and developed in this project.
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spelling ntu-10356/545062023-07-07T17:45:56Z Advertisement embedding for online videos Han, Wei. Yuan Junsong School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Nowadays, most existing online video players and websites provide search function. However, the search function can only be realized by key word matching. Often, a user want to search for videos that contain a certain object which is hard to describe in key words. In this situation, a search method using a query image as a key is needed. The method to find and locate a target object in a large collection of images or videos is called Visual Object Search. Visual Object Search can also be used for embedded online videos advertisement. It enables online video websites to efficiently and accurately embed advertisements of a commercial product to corresponding video frames that contain the commercial product. In this project, a video search algorithm was developed based on a Visual Object Search method using Randomized Visual Phrase via Random Partition, which is proposed and developed by a research team lead by Professor Yuan Junsong from NTU. A Windows 8 Store App was built implementing the video search algorithm. The App enables users to search and locate a query image in real time in a large collection of videos. The search result of the App is accurate enough for practical application. In addition, a video advertisement interface was also designed and developed in this project. Bachelor of Engineering 2013-06-21T04:15:27Z 2013-06-21T04:15:27Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/54506 en Nanyang Technological University 50 p. application/pdf
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Han, Wei.
Advertisement embedding for online videos
title Advertisement embedding for online videos
title_full Advertisement embedding for online videos
title_fullStr Advertisement embedding for online videos
title_full_unstemmed Advertisement embedding for online videos
title_short Advertisement embedding for online videos
title_sort advertisement embedding for online videos
topic DRNTU::Engineering::Electrical and electronic engineering
url http://hdl.handle.net/10356/54506
work_keys_str_mv AT hanwei advertisementembeddingforonlinevideos