Mohd Zaki, Hasan Firdaus and Shafait, Faisal and Mian, Ajmal S. (2017) Modeling sub-event dynamics in first-person action recognition. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 21st-26th July 2017, Honolulu, USA.
PDF
- Published Version
Restricted to Repository staff only Download (999kB) | Request a copy |
|
PDF (SCOPUS)
- Published Version
Restricted to Repository staff only Download (544kB) | Request a copy |
Abstract
First-person videos have unique characteristics such as heavy egocentric motion, strong preceding events, salient transitional activities and post-event impacts. Action recognition methods designed for third person videos may not optimally represent actions captured by first-person videos. We propose a method to represent the high level dynamics of sub-events in first-person videos by dynamically pooling features of sub-intervals of time series using a temporal feature pooling function. The sub-event dynamics are then temporally aligned to make a new series. To keep track of how the sub-event dynamics evolve over time, we recursively employ the Fast Fourier Transform on a pyramidal temporal structure. The Fourier coefficients of the segment define the overall video representation. We perform experiments on two existing benchmark first-person video datasets which have been captured in a controlled environment. Addressing this gap, we introduce a new dataset collected from YouTube which has a larger number of classes and a greater diversity of capture conditions thereby more closely depicting real-world challenges in first-person video analysis. We compare our method to state-of-the-art first person and generic video recognition algorithms. Our method consistently outperforms the nearest competitors by 10.3%, 3.3% and 11.7% respectively on the three datasets.
Item Type: | Conference or Workshop Item (Plenary Papers) |
---|---|
Additional Information: | 8923/64353 |
Uncontrolled Keywords: | First-person action recognition, deep learning |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering |
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Engineering > Department of Mechatronics Engineering |
Depositing User: | Dr. Hasan Firdaus Mohd Zaki |
Date Deposited: | 05 Jul 2018 14:56 |
Last Modified: | 05 Jul 2018 14:56 |
URI: | http://irep.iium.edu.my/id/eprint/64353 |
Actions (login required)
View Item |