System for optimal rapid serial visual presentation (RSVP) from user-specific neural brain signals
First Claim
1. A system for optimizing rapid serial visual presentation, the system comprising:
- one or more processors and a memory having instructions such that when the instructions are executed, the one or more processors perform operations of;
extracting a set of image features from a pair of images in a rapid serial visual presentation (RSVP) image set;
computing a predicted similarity metric for the pair of images using the set of image features to detect at least one similarity in the pair of images, wherein predicted similarity metrics are computed for all pairs of images in the RSVP image set;
sequencing the images in the RSVP image set according to the predicted similarity metrics, resulting in a sequenced set of images;
presenting the sequenced set of images and receiving neural brain signals during visualization of the sequenced set of images to detect a P300 signal;
computing a neural score for each image in the sequenced set of images based on the existence and strength of the P300 signal, wherein the neural score represents a dissimilarity between at least two images in the RSVP image set;
optimizing the system through a predictive model which models the neural scores computed for the sequenced set of images;
resequencing the images in the RSVP image set according to the predictive model and presenting the resequenced images; and
outputting an image sequence prediction which minimizes a false P300 signal.
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Abstract
Described is a system for optimizing rapid serial visual presentation (RSVP). A similarity metric is computed for RSVP images, and the images are sequenced according to the similarity metrics. The sequenced images are presented to a user, and neural signals are received to detect a P300 signal. A neural score for each image is computed, and the system is optimized to model the neural scores. The images are resequenced according a predictive model to output a sequence prediction which does not cause a false P300 signal. Additionally, the present invention describes computing a set of motion surprise maps from image chips. The image chips are labeled as static or moving and prepared into RSVP datasets. Neural signals are recorded in response to the RSVP datasets, and an EEG score is computed from the neural signals. Each image chip is then classified as containing or not containing an item of interest.
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Citations
12 Claims
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1. A system for optimizing rapid serial visual presentation, the system comprising:
one or more processors and a memory having instructions such that when the instructions are executed, the one or more processors perform operations of; extracting a set of image features from a pair of images in a rapid serial visual presentation (RSVP) image set; computing a predicted similarity metric for the pair of images using the set of image features to detect at least one similarity in the pair of images, wherein predicted similarity metrics are computed for all pairs of images in the RSVP image set; sequencing the images in the RSVP image set according to the predicted similarity metrics, resulting in a sequenced set of images; presenting the sequenced set of images and receiving neural brain signals during visualization of the sequenced set of images to detect a P300 signal; computing a neural score for each image in the sequenced set of images based on the existence and strength of the P300 signal, wherein the neural score represents a dissimilarity between at least two images in the RSVP image set; optimizing the system through a predictive model which models the neural scores computed for the sequenced set of images; resequencing the images in the RSVP image set according to the predictive model and presenting the resequenced images; and outputting an image sequence prediction which minimizes a false P300 signal. - View Dependent Claims (2, 3, 4)
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5. A computer-implemented method for optimizing rapid serial visual presentation, comprising an act of:
causing a data processor to perform operations of; extracting a set of image features from a pair of images in a rapid serial visual presentation (RSVP) image set; computing a predicted similarity metric for the pair of images using the set of image features to detect at least one similarity in the pair of images, wherein predicted similarity metrics are computed for all pairs of images in the RSVP image set; sequencing the images in the RSVP image set according to the predicted similarity metrics, resulting in a sequenced set of images; presenting the sequenced set of images and receiving neural brain signals during visualization of the sequenced set of images to detect a P300 signal; computing a neural score for each image in the sequenced set of images based on the existence and strength of the P300 signal, wherein the neural score represents a dissimilarity between at least two images in the RSVP image set; optimizing the system through a predictive model which models the neural scores computed for the sequenced set of images; resequencing the images in the RSVP image set according to the predictive model and presenting the resequenced images; and outputting an image sequence prediction which minimizes a false P300 signal. - View Dependent Claims (6, 7, 8)
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9. A computer program product for optimizing rapid serial visual presentation, the computer program product comprising:
computer-readable instruction means stored on a non-transitory computer-readable medium that are executable by a computer having a processor for causing the processor to perform operations of; extracting a set of image features from a pair of images in a rapid serial visual presentation (RSVP) image set; computing a predicted similarity metric for the pair of images using the set of image features to detect at least one similarity in the pair of images, wherein predicted similarity metrics are computed for all pairs of images in the RSVP image set; sequencing the images in the RSVP image set according to the predicted similarity metrics, resulting in a sequenced set of images; presenting the sequenced set of images and receiving neural brain signals during visualization of the sequenced set of images to detect a P300 signal; computing a neural score for each image in the sequenced set of images based on the existence and strength of the P300 signal, wherein the neural score represents a dissimilarity between at least two images in the RSVP image set; optimizing the system through a predictive model which models the neural scores computed for the sequenced set of images; resequencing the images in the RSVP image set according to the predictive model and presenting the resequenced images; and outputting an image sequence prediction which minimizes a false P300 signal. - View Dependent Claims (10, 11, 12)
Specification