Multimodal Location Estimation of Videos and Images

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.

Discusses localization of multimedia data Examines fundamental methods of establishing location metadata (other than GPS tagging) Covers Data-Driven as well as Semantic Location Estimation Includes supplementary material: sn.pub/extras

Autorentext
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

Inhalt
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.