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Activity Recognition in Egocentric Life-Logging Videos

Song, Sibo and Chandrasekhar, Vijay and Cheung, Ngai-Man and Narayan, Sanath and Li, Liyuan and Lim, Joo-Hwee (2015) Activity Recognition in Egocentric Life-Logging Videos. In: 12th Asian Conference on Computer Vision (ACCV), NOV 01-05, 2014, Singapore, SINGAPORE, pp. 445-458.

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Official URL: http://dx.doi.org/10.1007/978-3-319-16634-6_33


With the increasing availability of wearable cameras, research on first-person view videos (egocentric videos) has received much attention recently. While some effort has been devoted to collecting various egocentric video datasets, there has not been a focused effort in assembling one that could capture the diversity and complexity of activities related to life-logging, which is expected to be an important application for egocentric videos. In this work, we first conduct a comprehensive survey of existing egocentric video datasets. We observe that existing datasets do not emphasize activities relevant to the life-logging scenario. We build an egocentric video dataset dubbed LENA (Life-logging EgoceNtric Activities) (http://people.sutd.edu.sg/similar to 1000892/dataset) which includes egocentric videos of 13 fine-grained activity categories, recorded under diverse situations and environments using the Google Glass. Activities in LENA can also be grouped into 5 top-level categories to meet various needs and multiple demands for activities analysis research. We evaluate state-of-the-art activity recognition using LENA in detail and also analyze the performance of popular descriptors in egocentric activity recognition.

Item Type: Conference Proceedings
Series.: Lecture Notes in Computer Science
Additional Information: Copy right for this article belongs to the SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 05 Nov 2015 08:59
Last Modified: 05 Nov 2015 08:59
URI: http://eprints.iisc.ac.in/id/eprint/52700

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