Mobile visual product search and recommendation

Nowadays, computer vision is one of the popular developing fields which gives more effective data tracking and tracing services to the users. Hence, visual recognition based applications for the smartphone have drawn grown interest and demand by users lately. Although there are many studies of visua...

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Main Author: Aung, Thin Thin
Other Authors: Yap Kim Hui
Format: Final Year Project
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/10356/72116
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-721162023-07-07T17:22:19Z Mobile visual product search and recommendation Aung, Thin Thin Yap Kim Hui School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Nowadays, computer vision is one of the popular developing fields which gives more effective data tracking and tracing services to the users. Hence, visual recognition based applications for the smartphone have drawn grown interest and demand by users lately. Although there are many studies of visual recognition based applications in various areas, the study of visual recognition based application for artifacts is still not widely covered and developed yet. Therefore, this project mainly discusses the insight of visual recognition techniques and conducts experiments to observe the accuracy rate of the technique on artifacts. During this project, a small database with minimum criteria set is created and used for experiments. Moreover, Geometric Verification (GV), an alternative method which can reduce external noises such as illuminations changes, orientation changes and occlusions is introduced. After several experiments, results showed an increase of matching accuracy between 5 to 10% by this method. However, one of the disadvantages of this method is it required longer processing time for feature matching step. Lastly, various sets of experiments with different conditions are conducted with and without GV. Then, result analysis of the experiments are made and compared in term of processing time and accuracy rate. In conclusion, the possible ways to enhance the matching efficiency as well as to further test algorithm robustness for the future studies are discussed. Bachelor of Engineering 2017-05-26T02:47:36Z 2017-05-26T02:47:36Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/72116 en Nanyang Technological University 51 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Aung, Thin Thin
Mobile visual product search and recommendation
description Nowadays, computer vision is one of the popular developing fields which gives more effective data tracking and tracing services to the users. Hence, visual recognition based applications for the smartphone have drawn grown interest and demand by users lately. Although there are many studies of visual recognition based applications in various areas, the study of visual recognition based application for artifacts is still not widely covered and developed yet. Therefore, this project mainly discusses the insight of visual recognition techniques and conducts experiments to observe the accuracy rate of the technique on artifacts. During this project, a small database with minimum criteria set is created and used for experiments. Moreover, Geometric Verification (GV), an alternative method which can reduce external noises such as illuminations changes, orientation changes and occlusions is introduced. After several experiments, results showed an increase of matching accuracy between 5 to 10% by this method. However, one of the disadvantages of this method is it required longer processing time for feature matching step. Lastly, various sets of experiments with different conditions are conducted with and without GV. Then, result analysis of the experiments are made and compared in term of processing time and accuracy rate. In conclusion, the possible ways to enhance the matching efficiency as well as to further test algorithm robustness for the future studies are discussed.
author2 Yap Kim Hui
author_facet Yap Kim Hui
Aung, Thin Thin
format Final Year Project
author Aung, Thin Thin
author_sort Aung, Thin Thin
title Mobile visual product search and recommendation
title_short Mobile visual product search and recommendation
title_full Mobile visual product search and recommendation
title_fullStr Mobile visual product search and recommendation
title_full_unstemmed Mobile visual product search and recommendation
title_sort mobile visual product search and recommendation
publishDate 2017
url http://hdl.handle.net/10356/72116
_version_ 1772825798528466944