Paper
2 May 2017 Visual attention distracter insertion for improved EEG rapid serial visual presentation (RSVP) target stimuli detection
Author Affiliations +
Abstract
This paper† describes a technique in which we improve upon the prior performance of the Rapid Serial Visual Presentation (RSVP) EEG paradigm for image classification though the insertion of visual attention distracters and overall sequence reordering based upon the expected ratio of rare to common “events” in the environment and operational context. Inserting distracter images maintains the ratio of common events to rare events at an ideal level, maximizing the rare event detection via P300 EEG response to the RSVP stimuli. The method has two steps: first, we compute the optimal number of distracters needed for an RSVP stimuli based on the desired sequence length and expected number of targets and insert the distracters into the RSVP sequence, and then we reorder the RSVP sequence to maximize P300 detection. We show that by reducing the ratio of target events to nontarget events using this method, we can allow RSVP sequences with more targets without sacrificing area under the ROC curve (azimuth).
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Deepak Khosla, David J. Huber, and Kevin Martin "Visual attention distracter insertion for improved EEG rapid serial visual presentation (RSVP) target stimuli detection", Proc. SPIE 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, 102000Y (2 May 2017); https://doi.org/10.1117/12.2262913
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Electroencephalography

Target detection

Video

Image analysis

Brain

Detection and tracking algorithms

Signal detection

Back to Top