STARE: spatio-temporal attention relocation for multiple structured activities detection

Kyuhwa Lee, Dimitri Ognibene, Hyung Jin Chang, Tae-kyun Kim, Yiannis Demiris

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)5916-5927
Number of pages12
JournalIEEE Transactions on Image Processing
Issue number12
Early online date7 Oct 2015
Publication statusPublished - Dec 2015


  • Activity detection
  • visual attention
  • resource allocation
  • stochastic context-free grammars


Dive into the research topics of 'STARE: spatio-temporal attention relocation for multiple structured activities detection'. Together they form a unique fingerprint.

Cite this