Augmented Visual Intelligence

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Augmented Visual Intelligence
Title:
Augmented Visual Intelligence
Journal Title:
TENCON 2015 - 2015 IEEE Region 10 Conference
Keywords:
Publication Date:
01 November 2015
Citation:
J. H. Lim, "Augmented Visual Intelligence," TENCON 2015 - 2015 IEEE Region 10 Conference, Macao, 2015, pp. 1-6. doi: 10.1109/TENCON.2015.7373017
Abstract:
We propose an Augmented Visual Intelligence (AVI) framework to assist human in vision- and memory-related tasks. The AVI framework exploits wearable cameras and ambient computing facilities to empower a user's vision and memory functions by answering four types of queries central to visual activities. In particular, the Extended Visual Memory (EVM) model plays a central role in AVI. Learning of EVM stores view-based visual fragments (VF), which are abstracted into high-level visual schemas (VS), both in the visual long-term memory. During inference, the visual short-term memory plays a key role in the schematic representations of, and the similarity computation between, a visual input and a VF, exemplified from VS when necessary. In this paper, we describe the AVI framework and the EVM model followed by an implementation scenario on assisted living.
License type:
PublisherCopyrights
Funding Info:
Description:
(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
ISSN:
2159-3442
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