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.
Full text not available from this repository. (Request a copy)Abstract
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 |
| Publisher: | SPRINGER-VERLAG BERLIN |
| 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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