DETECTING AND LABELING PLACES USING RUNTIME CHANGE-POINT DETECTION AND PLACE LABELING CLASSIFIERS
First Claim
1. A computer implemented method for labeling places captured in a video stream, the method comprising:
- receiving a video stream comprising multiple digital representations of images;
generating a measurement stream representing the video stream, wherein the measurement stream comprises one or more image histograms of the video stream;
segmenting the measurement stream into a plurality of segments corresponding to types of places in the video stream based on the histograms of the videos stream, wherein the boundary between two adjacent segments represents a change-point of the measurement stream at a time-step;
computing probability distributions of the segments over a plurality of place classifiers, wherein probability of a segment represents a likelihood that the segment is classified by a place classifier of the plurality of the place classifiers; and
generating place labels for the types of places in video stream based on probabilities of change-points of the measurement stream, wherein the change-points are detected based on the probability distributions of the segments over the plurality of the place classifiers.
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Abstract
A system and method are disclosed for detecting and labeling places in a video stream using change-points detection. The system comprises a place label generation module configured to assign place labels probabilistically to places in the video stream based on the measurements of the measurement stream representing the video. For each measurement in the segment, the place label generation module classifies the measurement by computing the probability of the measurement being classified by a learned Gaussian Process classifier. Based on the probabilities generated with respect to all the measurements in the segment, the place label generation module determines the place label for the segment. In cases where a Gaussian Process classifier cannot positively classify a segment, the place label generation module determines whether the segment corresponds to an unknown place based on the perplexity statistics of the classification and a threshold value.
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Citations
35 Claims
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1. A computer implemented method for labeling places captured in a video stream, the method comprising:
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receiving a video stream comprising multiple digital representations of images; generating a measurement stream representing the video stream, wherein the measurement stream comprises one or more image histograms of the video stream; segmenting the measurement stream into a plurality of segments corresponding to types of places in the video stream based on the histograms of the videos stream, wherein the boundary between two adjacent segments represents a change-point of the measurement stream at a time-step; computing probability distributions of the segments over a plurality of place classifiers, wherein probability of a segment represents a likelihood that the segment is classified by a place classifier of the plurality of the place classifiers; and generating place labels for the types of places in video stream based on probabilities of change-points of the measurement stream, wherein the change-points are detected based on the probability distributions of the segments over the plurality of the place classifiers. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A computer system for labeling places captured in a video stream, the system comprising:
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a segmentation module configured to; receive a video stream comprising multiple digital representations of images; generate a measurement stream representing the video stream, wherein the measurement stream comprises one or more image histograms of the video stream; segment the measurement stream into a plurality of segments corresponding to types of places in the video stream based on the histograms of the videos stream, wherein the boundary between two adjacent segments represents a change-point of the measurement stream at a time-step; compute probability distributions of the segments over a plurality of place classifiers, wherein probability of a segment represents a likelihood that the segment is classified by a place classifier of the plurality of the place classifiers; and a place label generation module configured to; generate place labels for the types of places in video stream based on probabilities of change-points of the measurement stream, wherein the change-points are detected based on the probability distributions of the segments over the plurality of the place classifiers. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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25. A computer program product for labeling places captured in a video stream, the computer program product comprising a non-statutory computer-readable medium containing computer program code for performing the operations:
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receiving a video stream comprising multiple digital representations of images; generating a measurement stream representing the video stream, wherein the measurement stream comprises one or more image histograms of the video stream; segmenting the measurement stream into a plurality of segments corresponding to types of places in the video stream based on the histograms of the videos stream, wherein the boundary between two adjacent segments represents a change-point of the measurement stream at a time-step; computing probability distributions of the segments over a plurality of place classifiers, wherein probability of a segment represents a likelihood that the segment is classified by a place classifier of the plurality of the place classifiers; and generating place labels for the types of places in video stream based on probabilities of change-points of the measurement stream, wherein the change-points are detected based on the probability distributions of the segments over the plurality of the place classifiers. - View Dependent Claims (26, 27, 28, 29, 30, 31, 32, 33, 34, 35)
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Specification