We present a spatio-temporal attention relocation (STARE) method, an information-theoretic approach for efficient detection of simultaneously occurring structured activities. Given multiple human activities in a scene, our method dynamically focuses on the currently most informative activity. Each activity can be detected without complete observation, as the structure of sequential actions plays an important role on making the system robust to unattended observations. For such systems, the ability to decide where and when to focus is crucial to achieving high detection performances under resource bounded condition. Our main contributions can be summarized as follows: 1) information-theoretic dynamic attention relocation framework that allows the detection of multiple activities efficiently by exploiting the activity structure information and 2) a new high-resolution data set of temporally-structured concurrent activities. Our experiments on applications show that the STARE method performs efficiently while maintaining a reasonable level of accuracy.

Lee, K., Ognibene, D., Chang Hyung, J., Kim, T., Demiris, Y. (2015). STARE: Spatio-Temporal Attention Relocation for Multiple Structured Activities Detection. IEEE TRANSACTIONS ON IMAGE PROCESSING, 41(10), 1267-1274 [10.1109/TIP.2015.2487837].

STARE: Spatio-Temporal Attention Relocation for Multiple Structured Activities Detection

Ognibene D
Secondo
;
2015

Abstract

We present a spatio-temporal attention relocation (STARE) method, an information-theoretic approach for efficient detection of simultaneously occurring structured activities. Given multiple human activities in a scene, our method dynamically focuses on the currently most informative activity. Each activity can be detected without complete observation, as the structure of sequential actions plays an important role on making the system robust to unattended observations. For such systems, the ability to decide where and when to focus is crucial to achieving high detection performances under resource bounded condition. Our main contributions can be summarized as follows: 1) information-theoretic dynamic attention relocation framework that allows the detection of multiple activities efficiently by exploiting the activity structure information and 2) a new high-resolution data set of temporally-structured concurrent activities. Our experiments on applications show that the STARE method performs efficiently while maintaining a reasonable level of accuracy.
Articolo in rivista - Articolo scientifico
Activity detection; visual attention; resource allocation; stochastic context-free grammars;
English
2015
41
10
1267
1274
reserved
Lee, K., Ognibene, D., Chang Hyung, J., Kim, T., Demiris, Y. (2015). STARE: Spatio-Temporal Attention Relocation for Multiple Structured Activities Detection. IEEE TRANSACTIONS ON IMAGE PROCESSING, 41(10), 1267-1274 [10.1109/TIP.2015.2487837].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/301937
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