Mobile product recognition for information retrieval
Mobile applications are becoming increasingly popular as it can be easily downloaded and installed onto smartphone. It is also convenient to use as a smartphone itself is a portable device. Image recognition is one possible and useful application that can be developed. Even though the title of the p...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2013
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| Online Access: | http://hdl.handle.net/10356/53157 |
| _version_ | 1826118451100385280 |
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| author | Ng, Yu Tian. |
| author2 | Yap Kim Hui |
| author_facet | Yap Kim Hui Ng, Yu Tian. |
| author_sort | Ng, Yu Tian. |
| collection | NTU |
| description | Mobile applications are becoming increasingly popular as it can be easily downloaded and installed onto smartphone. It is also convenient to use as a smartphone itself is a portable device. Image recognition is one possible and useful application that can be developed. Even though the title of the project is Product Recognition, the actual project is on Landmark recognition. As the basis of the project is the same, hence the database used will not have significant impact on the project. In this project, the theory of the Bag-of-Words framework is covered and the performances of different sampling methods are evaluated though experiment. Scale-Invariant Feature Transform (SIFT) is chosen as the descriptor, with the Difference-of-Gaussian function as the detector for keypoint sampling. In summary, the dense sampling performs better than keypoint sampling. |
| first_indexed | 2024-10-01T04:43:55Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/53157 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:43:55Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/531572023-07-07T16:15:20Z Mobile product recognition for information retrieval Ng, Yu Tian. Yap Kim Hui School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Mobile applications are becoming increasingly popular as it can be easily downloaded and installed onto smartphone. It is also convenient to use as a smartphone itself is a portable device. Image recognition is one possible and useful application that can be developed. Even though the title of the project is Product Recognition, the actual project is on Landmark recognition. As the basis of the project is the same, hence the database used will not have significant impact on the project. In this project, the theory of the Bag-of-Words framework is covered and the performances of different sampling methods are evaluated though experiment. Scale-Invariant Feature Transform (SIFT) is chosen as the descriptor, with the Difference-of-Gaussian function as the detector for keypoint sampling. In summary, the dense sampling performs better than keypoint sampling. Bachelor of Engineering 2013-05-30T04:28:21Z 2013-05-30T04:28:21Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/53157 en Nanyang Technological University 31 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering Ng, Yu Tian. Mobile product recognition for information retrieval |
| title | Mobile product recognition for information retrieval |
| title_full | Mobile product recognition for information retrieval |
| title_fullStr | Mobile product recognition for information retrieval |
| title_full_unstemmed | Mobile product recognition for information retrieval |
| title_short | Mobile product recognition for information retrieval |
| title_sort | mobile product recognition for information retrieval |
| topic | DRNTU::Engineering::Electrical and electronic engineering |
| url | http://hdl.handle.net/10356/53157 |
| work_keys_str_mv | AT ngyutian mobileproductrecognitionforinformationretrieval |