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  1. Proceedings of the 2016 ACM workshop on Vision and Language Integration Meets Multimedia Fusion (iV&L-MM '16)
  2. Semantic Indexing of Wearable Camera Images: Kids'Cam Concepts
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Exploiting Scene Context for Image Captioning
News Event Understanding by Mining Latent Factors From Multimodal Tensors
Jointly Representing Images and Text: Dependency Graphs, Word Senses, and Multimodal Embeddings
Multimodal and Crossmodal Representation Learning from Textual and Visual Features with Bidirectional Deep Neural Networks for Video Hyperlinking
Beyond Language and Vision, Towards Truly Multimedia Integration
Cross-modal Classification by Completing Unimodal Representations
User Video Summarization Based on Joint Visual and Semantic Affinity Graph
Semantic Indexing of Wearable Camera Images: Kids'Cam Concepts
Disinformation in Multimedia Annotation: Misleading Metadata Detection on YouTube

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Semantic Indexing of Wearable Camera Images: Kids'Cam Concepts

Content Provider ACM Digital Library
Author O'Connor, Noel E. Wang, Peng Barr, Michelle McGuinness, Kevin Signal, Louise Chambers, Tim Zhou, Jiang Freitas, Andre Azevedo, Lucas Ní Mhurchu, Cliona Stanley, James Gurrin, Cathal Smith, Moira Smeaton, Alan F. Davis, Brian
Abstract In order to provide content-based search on image media, including images and video, they are typically accessed based on manual or automatically assigned concepts or tags, or sometimes based on image-image similarity depending on the use case. While great progress has been made in very recent years in automatic concept detection using machine learning, we are still left with a mis-match between the semantics of the concepts we can automatically detect, and the semantics of the words used in a user's query, for example. In this paper we report on a large collection of images from wearable cameras gathered as part of the Kids'Cam project, which have been both manually annotated from a vocabulary of 83 concepts, and automatically annotated from a vocabulary of 1,000 concepts. This collection allows us to explore issues around how language, in the form of two distinct concept vocabularies or spaces, one manually assigned and thus forming a ground-truth, is used to represent images, in our case taken using wearable cameras. It also allows us to discuss, in general terms, issues around mis-match of concepts in visual media, which derive from language mis-matches. We report the data processing we have completed on this collection and some of our initial experimentation in mapping across the two language vocabularies.
Starting Page 27
Ending Page 34
Page Count 8
File Format PDF
ISBN 9781450345194
DOI 10.1145/2983563.2983566
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2016-10-16
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Lifelogging Wearable cameras Concept vocabularies Image tagging
Content Type Text
Resource Type Article
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