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Computer vision for lifelogging

Wang, Peng, Sun, Lifeng, Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389, Gurrin, Cathal orcid logoORCID: 0000-0003-2903-3968 and Yang, Shiqiang (2018) Computer vision for lifelogging. In: Marco, Leo and Farinella, Giovanni Maria, (eds.) Computer Vision for Assistive Healthcare. A volume in Computer Vision and Pattern Recognition . Academic Press, pp. 249-282. ISBN 9780128134467

The rapid development of mobile devices capable of sensing our interaction with the environment has make it possible to assist humans in daily living such as helping patients with cognitive impairment or providing customized food intake plan for patients with obesity, etc. All of this can be achieved through the passive gathering of detailed records of everyday behaviour which is termed as lifelogging. For example, the widely adopted smart mobiles and newly-emerging consumer wearable devices like Google glass, Baidu eye, Narrative clip, etc. are usually embedded with rich sensing capabilities including camera, accelerometer, GPS, digital compass, etc. which can help to capture daily activity unobtrusively. Among such heterogeneous sensor readings, visual media contain more semantics to assist in characterizing everyday activities and visual lifelogging is a class of personal sensing which employs wearable cameras to capture image or video sequences of everyday activities. This chapter will focus on the most recent research methods in understanding visual lifelogs, including semantic annotations of visual concepts, utilization of contextual semantics, recognition of activities, visualization of activities, etc. We also discuss some research challenges which indicates potential directions for future research. This chapter is intended to support readers in the area of assistive living using wearable sensing, computer vision for lifelogging, human behaviour researchers aiming at behavioural analysis based on visual understanding.
Item Type:Book Section
Uncontrolled Keywords:computer vision
Subjects:Computer Science > Lifelog
Computer Science > Machine learning
Computer Science > Digital video
Computer Science > Image processing
DCU Faculties and Centres:Research Institutes and Centres > INSIGHT Centre for Data Analytics
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Publisher:Academic Press
Official URL:https://doi.org/10.1016/B978-0-12-813445-0.00009-5
Copyright Information:© 2018 Academic Press
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Natural Science Foundation of China under Grant No. 61502264, 61210008, Science Foundation Ireland SFI/12/RC/2289.
ID Code:22378
Deposited On:29 May 2018 15:39 by Alan Smeaton . Last Modified 18 Dec 2019 12:18

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