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  1. Proceedings of the 1st Conference on Novel Gaze-Controlled Applications (NGCA '11)
  2. Exploring interaction modes for image retrieval
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Designing gaze-supported multimodal interactions for the exploration of large image collections
Mobile gaze-based screen interaction in 3D environments
Eye tracking within the packaging design workflow: interaction with physical and virtual shelves
Towards intelligent user interfaces: anticipating actions in computer games
Hyakunin-Eyesshu: a tabletop Hyakunin-Isshu game with computer opponent by the action prediction based on gaze detection
Comparison of gaze-to-objects mapping algorithms
Evaluation of a remote webcam-based eye tracker
An open-source low-cost eye-tracking system for portable real-time and offline tracking
Gaze and voice controlled drawing
Exploring interaction modes for image retrieval
Gaze interaction from bed

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Exploring interaction modes for image retrieval

Content Provider ACM Digital Library
Author Engelman, Corey Li, Rui Pelz, Jeff Haake, Anne Shi, Pengcheng
Abstract The number of digital images in use is growing at an increasing rate across a wide array of application domains. That being said, there is an ever-growing need for innovative ways to help endusers gain access to these images quickly and effectively. Moreover, it is becoming increasingly more difficult to manually annotate these images, for example with text labels, to generate useful metadata. One such method for helping users gain access to digital images is content-based image retrieval (CBIR). Practical use of CBIR systems has been limited by several "gaps", including the well-known semantic gap and usability gaps [1]. Innovative designs are needed to bring end users into the loop to bridge these gaps. Our human-centered approaches integrate human perception and multimodal interaction to facilitate more usable and effective image retrieval. Here we show that multi-touch interaction is more usable than gaze based interaction for explicit image region selection.
Starting Page 1
Ending Page 4
Page Count 4
File Format PDF
ISBN 9781450306805
DOI 10.1145/1983302.1983312
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2011-05-26
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Multimodal Image retrieval Human-centered computing Eye tracking
Content Type Text
Resource Type Article
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