Conference item
Thread-safe: towards recognizing human actions across shot boundaries
- Abstract:
-
We study the task of recognizing human actions in video whilst paying attention to the shot and thread editing structure. Most existing action recognition algorithms ignore this structure, but it is generally present in edited TV and film material.
To this end, we make the following contributions: first, we introduce a new dataset of human actions to study the occurrence/reoccurrence of patterns of human actions in edited TV material; second, we propose composing a video into threads of related shots, removing some of the discontinuities due to shot boundaries; and third, we show the benefits of utilizing video threads in recognizing human actions. The experiments demonstrate that human action retrieval accuracy can be improved using threads.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 746.1KB, Terms of use)
-
- Publisher copy:
- 10.1007/978-3-319-16817-3_15
Authors
- Funder identifier:
- https://ror.org/0439y7842
- Grant:
- EP/I012001/1
- Publisher:
- Springer
- Host title:
- Computer Vision -ACCV 2014
- Pages:
- 222-237
- Series:
- Lecture Notes in Computer Science
- Series number:
- 9006
- Publication date:
- 2015-04-17
- Acceptance date:
- 2014-11-01
- Event title:
- 12th Asian Conference on Computer Vision (ACCV 2014)
- Event location:
- Singapore
- Event start date:
- 2014-11-01
- Event end date:
- 2014-11-05
- DOI:
- EISSN:
-
1611-3349
- ISBN:
- 9783319168166
- Language:
-
English
- Keywords:
- Pubs id:
-
572816
- Local pid:
-
pubs:572816
- Deposit date:
-
2024-07-12
Terms of use
- Copyright holder:
- Springer International Publishing Switzerland
- Copyright date:
- 2015
- Rights statement:
- © 2015 Springer International Publishing Switzerland
- Notes:
- This is the accepted manuscript version of the article. The final version is available online from Springer at https://dx.doi.org/10.1007/978-3-319-16817-3_15
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