Search | JOV | ARVO Journals

Access Provided By:
MIT Libraries

Forgot password?

Create an Account

View

Showing 1 – 6 of 6

SORT: Best Match Most Recent Oldest

VIEW: Basic | Expanded

Vision Sciences Society Annual Meeting Abstract September 2021

Features derived from a deep neural network distinguish visual cues used by CCTV experts versus novices

Yujia Peng; Joseph Burling; Greta Todorova; Hongjing Lu; Frank Pollick

Journal of Vision. 2021; 21(9):1965. https://doi.org/10.1167/jov.21.9.1965

Vision Sciences Society Annual Meeting Abstract September 2018

Linking action words and body movements: Evidence from behavioral oscillations

Hannah Lee; Joseph Burling; Hongjing Lu

Journal of Vision. 2018; 18(10):52. https://doi.org/10.1167/18.10.52

Vision Sciences Society Annual Meeting Abstract August 2017

Categorizing features of coordination from joint actions

Joseph Burling; Hongjing Lu

Journal of Vision. 2017; 17(10):63. https://doi.org/10.1167/17.10.63

Vision Sciences Society Annual Meeting Abstract August 2017

The importance of gaze coherence of CCTV operators in facilitating the ability to recognise harmful intentions

Greta Todorova; Joseph Burling; Hongjing Lu; Frank Pollick

Journal of Vision. 2017; 17(10):546. https://doi.org/10.1167/17.10.546

Vision Sciences Society Annual Meeting Abstract September 2016

A comparison of eye-movement patterns between experienced observers and novices in detecting harmful intention from surveillance video

Joseph Burling; Hongjing Lu; Greta Todorova; Frank Pollick

Journal of Vision. 2016; 16(12):1340. https://doi.org/10.1167/16.12.1340

Vision Sciences Society Annual Meeting Abstract September 2016

Recognizing harmful intent from surveillance video viewed through the eye-movements of novice and experienced observers

Frank Pollick; Greta Todorova; Steven Thurman; Joseph Burling; Hongjing Lu

Journal of Vision. 2016; 16(12):1342. https://doi.org/10.1167/16.12.1342

Advertisement