Multimodal Location Estimation of Videos and Images
Published on 24. September 2016
Book
Paperback/Softback
XII, 191 pages
978-3-319-34529-1 (ISBN)
Description
This book presents an overview of the field of multimodal location estimation. The authors' aim is to describe the research results in this field in a unified way. The book describes fundamental methods of acoustic, visual, textual, social graph, and metadata processing as well as multimodal integration methods used for location estimation. In addition, the book covers benchmark metrics and explores the limits of the technology based on a human baseline. The book also outlines privacy implications and discusses directions for future research in the area.
More details
Edition
Softcover reprint of the original 1st ed. 2015
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
80 farbige Abbildungen
XII, 191 p. 80 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 11 mm
Weight
355 gr
ISBN-13
978-3-319-34529-1 (9783319345291)
DOI
10.1007/978-3-319-09861-6
Schweitzer Classification
Other editions
Additional editions
Jaeyoung Choi | Gerald Friedland
Multimodal Location Estimation of Videos and Images
Book
10/2014
Springer
€106.99
Shipment within 10-15 days
Persons
Dr. Gerald Friedland is the Director at the Audio and Multimedia Research, International Computer Science Institute
Dr. Jaeyoung Chois is a Researcher at the Audio and Multimedia Research, International Computer Science Institute
Dr. Jaeyoung Chois is a Researcher at the Audio and Multimedia Research, International Computer Science Institute
Content
Introduction.- The Benchmark as a Research Catalyst: Charting the Progress of Geo-Prediction for Social Multimedia.- Large-scale Image Geolocalization.- Vision-based Fine-Grained Location Estimation.- Image-Based Positioning of Mobile Devices in Indoor Environments.- Application of Large-Scale Classification Techniques for Simple Location Estimation Experiments.- Collaborative Multimodal Location Estimation of Consumer Media.- Georeferencing Flickr resources based on multimodal features.- Human vs Machine: Establishing a Human Baseline for Multimodal Location Estimation.- Personalized Travel Navigation and Photo-Shooting Navigation Using Large-Scale Geotags.