Search-based automatic image annotation using geotagged community photos:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
2014
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| Schlagworte: | |
| Online-Zugang: | Volltext Volltext Inhaltsverzeichnis |
| Beschreibung: | XVII, 151 S. Ill., graph. Darst. |
Internformat
MARC
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Datensatz im Suchindex
| _version_ | 1804152655539339264 |
|---|---|
| adam_text | Contents
Abstract iii
Resumé
v
Zusammenfassung
vii
List of Figures
xiii
List of Tables
xvii
I Motivation and State-of-the-Art
1
1
Introduction
3
1.1
The Context
.................................. 3
1.2
Automatic Image Annotation
......................... 6
1.3
The Challenges
. . ·............................... 7
1.4
The Solution
.................................. 7
1.5
Structure of the Thesis
.............................
Π
2
Related Work
13
2.1
Introduction
................................... 13
2.2
Content-based Image Retrieval
........................ 14
2.3
Model-based Automatic Image Annotation
................. 16
2.4
Search-based Automatic Image Annotation
. . ............... 17
2.4.1
The World Wide Web as Annotation Resource
........... 19
2.4.2
Community Photos as Annotation Resource
............. 22
2.4.2.1
Classification-based Approaches
.............. 22
2.4.2.2
Semi-automatic Approaches
................. 23
2.4.2.3
AIA
using Spatial and Temporal Contexts
........ 24
2.4.2.4
AIA
using Social Context
.................. 27
2.5
Related Work around Search-based Image Annotation
........... 29
2.5.1
Geo-based Photo Crawling
...................... 29
2.5.2
Resolving Tag Ambiguity
....................... 30
2.5.3
Improving Image Matching
......................34
2.6
Thesis Contributions Revisited
........................ 35
II Data Preparation and Tag Disambiguation
37
3
Geographical Crawling and Indexing of Community Photos
39
3.1
Introduction
................................... 39
3.2
Geo-based Data Crawling
........................... 40
3.3
Tag Cleaning
.................................. 42
3.4
Indexing using Quad-tree
........................... 45
3.5
Qualitative Insight
............................... 47
3.6
Summary
..........,.......................... 49
4
Mining Tag Relatedness for Resolving Tag Ambiguity
51
4.1
Introduction
................................... 51
4.2
Tag Relatedness Approach
........................... 53
4.2.1
Approach Overview
.......................... 53
4.2.2
Feature Selection for Tag Relatedness
................ 54
4.2.3
Tag Probability Distribution
......................... 60
4.2.4
Distance Measure
............................ 61
4.3
Evaluation
.................................... 65
4.3.1
Dataset
................................. 65
4.3.2
Qualitative Insight
........................... 65
4.3.3
Semantic Grounding using WordNet
................. 67
4.3.4
Evaluation using Large Scale Co-occurrence Statistics
....... 69
4.4
Resolving Tag Ambiguity
........................... 73
4.5
Summary
.................................... 76
III Improving SURF-based Image Matching
77
5
Classification-based
Keypoint
Pruning
79
5.1
Introduction
...................... ............. 79
5.2 Keypoint
Pruning using Visual Attention Models
.............. 81
5.3 Keypoint
Pruning as Classification Problem
................. 82
5.3.1
Training
Dataset
............................ 83
5.3.2
Classification Features
......................... 85
5.3.3
Classification Using Random Forest
................. 87
5.4
Experimental Evaluation
............................ 88
5.4.1
Classification Performance
....................... 88
5.4.2
Effectiveness of
Keypoint
Pruning
.................. 89
5.4.3
Runtime Evaluation
.......................... 92
5.5
Summary
.................................... 96
6
SURF-based Iterative Image Matching
99
6.1
Introduction
................................... 99
6.2
Iterative Image Matching
...........................100
6.3
Experimental
Evaluation............................102
6.3.1
Dataset
..........·.··> .................... 102
6.3.2 Evaluation
Methodology
........................103
6.3.3
Results
.................................104
6.4
Summary
..................................... 105
IV Tag Ranking and Global Evaluation
107
7
Probabilistic Model for Tag Ranking
109
7.1
Introduction
...................................109
7.2
Problem Statement
............................... 109
7.3
Pseudo-generative Statistical Model
.....................
Ill
7.3.1
Estimating Image-to-image Relevance:
Р(1ј Дп)
..........113
7.3.2
Estimating Word-to-image Relevance: P{t% Ij)
...........114
7.4
Summary
....................................116
8
Experimental Evaluation
117
8.1
Setup and Evaluation Procedure
.......................117
8.2
Evaluation Metrics
...............................118
8.3
Compared
AIA
Models
.............................118
8.4
Results Discussion
...............................119
8.4.1
Thesis Approach
(TA)
vs. Baseline (BL) Methods
.........120
8.4.2
Effectiveness of Tag Refinement
....................122
8.5
Summary
....................................124
9
Conclusion and Future Work
125
9.1
Summary of Research
.............................125
9.1.1
Two-Phase Automatic Image Annotation Approach
........125
9.1.2
Geo-based Data Crawling and Indexing
...............126
9.1.3
Resolving Tag Ambiguity
.......................126
9.1.4
Improving SURF-based Image Matching
...............127
9.1.5
Tag Ranking
..............................128
9.2
Future Work
..................................128
Bibliography
131
|
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| spelling | Mousselly Sergieh, Hatem Verfasser aut Search-based automatic image annotation using geotagged community photos Hatem Mousselly Sergieh 2014 XVII, 151 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Passau, Lyon, Univ., Diss. cotutelle, 2014 Flickr (DE-588)7669185-8 gnd rswk-swf Annotation (DE-588)4560829-5 gnd rswk-swf Social Tagging (DE-588)7629989-2 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Social Tagging (DE-588)7629989-2 s Flickr (DE-588)7669185-8 s Annotation (DE-588)4560829-5 s DE-604 http://www.opus-bayern.de/uni-passau/volltexte/2014/2738/ kostenfrei Volltext https://nbn-resolving.org/urn:nbn:de:bvb:739-opus-27387 Resolving-System Volltext Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027598801&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Mousselly Sergieh, Hatem Search-based automatic image annotation using geotagged community photos Flickr (DE-588)7669185-8 gnd Annotation (DE-588)4560829-5 gnd Social Tagging (DE-588)7629989-2 gnd |
| subject_GND | (DE-588)7669185-8 (DE-588)4560829-5 (DE-588)7629989-2 (DE-588)4113937-9 |
| title | Search-based automatic image annotation using geotagged community photos |
| title_auth | Search-based automatic image annotation using geotagged community photos |
| title_exact_search | Search-based automatic image annotation using geotagged community photos |
| title_full | Search-based automatic image annotation using geotagged community photos Hatem Mousselly Sergieh |
| title_fullStr | Search-based automatic image annotation using geotagged community photos Hatem Mousselly Sergieh |
| title_full_unstemmed | Search-based automatic image annotation using geotagged community photos Hatem Mousselly Sergieh |
| title_short | Search-based automatic image annotation using geotagged community photos |
| title_sort | search based automatic image annotation using geotagged community photos |
| topic | Flickr (DE-588)7669185-8 gnd Annotation (DE-588)4560829-5 gnd Social Tagging (DE-588)7629989-2 gnd |
| topic_facet | Flickr Annotation Social Tagging Hochschulschrift |
| url | http://www.opus-bayern.de/uni-passau/volltexte/2014/2738/ https://nbn-resolving.org/urn:nbn:de:bvb:739-opus-27387 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027598801&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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