The Impact of Image Resolution on the Precision of Content-based Retrieval
| Thesis title in Czech: | Vliv rozlišení obrázku na přesnost vyhledávání podle obsahu |
|---|---|
| Thesis title in English: | The Impact of Image Resolution on the Precision of Content-based Retrieval |
| Key words: | Podobnostní vyhledávání, vyhledávání v obrázcích, rozlišení obrázku, signatury, SIFT, SURF, VLAD, BoW |
| English key words: | Similarity search, image retrieval, image resolution, feature signatures, SIFT, SURF, VLAD, BoW |
| Academic year of topic announcement: | 2014/2015 |
| Thesis type: | diploma thesis |
| Thesis language: | angličtina |
| Department: | Department of Software Engineering (32-KSI) |
| Supervisor: | doc. RNDr. Jakub Lokoč, Ph.D. |
| Author: | hidden - assigned and confirmed by the Study Dept. |
| Date of registration: | 19.02.2015 |
| Date of assignment: | 19.02.2015 |
| Confirmed by Study dept. on: | 10.03.2015 |
| Date and time of defence: | 09.09.2015 09:30 |
| Date of electronic submission: | 30.07.2015 |
| Date of submission of printed version: | 31.07.2015 |
| Date of proceeded defence: | 09.09.2015 |
| Opponents: | prof. RNDr. Tomáš Skopal, Ph.D. |
| Guidelines |
| The goal of this thesis is to compare two content-based image retrieval approaches - bag of features based models and feature signature based models. Author should evaluate retrieval precision of given similarity models depending on resolution of input images and try to find optimal configuration of the models for different image resolutions and data sets. Experiments should be performed on several different benchmark datasets commonly used in image retrieval. The main comparison should be made between signature based model based on PCT descriptors and SQFD distance and BoW based models with SIFT/SURF descriptors. |
| References |
| Introduction to Information Retrieval
C. D. Manning, P. Raghavan, and H. Schutze. Cambridge University Press, 2008 Distinctive image features from scale-invariant keypoints David G. Lowe. International Journal of Computer Vision, 2004 Aggregating local images descriptors into compact codes H. Jégou, F. Perronnin, M. Douze, J. Sanchez, P. Pérez and C. Schmid. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012 Object retrieval with large vocabularies and fast spatial matching J. Philbin, O. Chum, M. Isard, J. Sivic, A. Zisserman. CVPR, 2007 Visual Image Search: Feature Signatures or/and Global Descriptors J. Lokoč, D. Novák, M. Batko, T. Skopal. SISAP, 2012 |