METHOD AND APPARATUS FOR DETECTING ABNORMAL MOVEMENT
First Claim
1. An apparatus for detecting an abnormal movement, the apparatus comprising:
- a feature tracing unit, as executed by a processor, configured to extract features of a moving object in an input image, trace a variation in a position of the extracted features according to time, and ascertain trajectories of the extracted features;
a topic online learning unit configured to classify the input image in units of documents that are bundles of the trajectories, and ascertain, by using an online learning method which is a probabilistic topic model, probability distribution states of topics included in a classified document; and
a movement pattern online learning unit configured to learn a velocity and a direction for each of the ascertained topics, and learn a movement pattern by inferring a spatiotemporal correlation between the ascertained topics.
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Abstract
Provided are a method and apparatus for detecting an abnormal movement. The apparatus includes a feature tracing unit configured to extract features of a moving object in an input image, trace a variation in position of the extracted features according to time, and ascertain trajectories of the extracted features; a topic online learning unit configured to classify the input image in units of documents which are bundles of the trajectories, and ascertain probability distribution states of topics, which constitute the classified document, by using an online learning method which is a probabilistic topic model; and a movement pattern online learning unit configured to learn a velocity and a direction for each of the ascertained topics, and learn a movement pattern by inferring a spatiotemporal correlation between the ascertained topics.
26 Citations
23 Claims
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1. An apparatus for detecting an abnormal movement, the apparatus comprising:
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a feature tracing unit, as executed by a processor, configured to extract features of a moving object in an input image, trace a variation in a position of the extracted features according to time, and ascertain trajectories of the extracted features; a topic online learning unit configured to classify the input image in units of documents that are bundles of the trajectories, and ascertain, by using an online learning method which is a probabilistic topic model, probability distribution states of topics included in a classified document; and a movement pattern online learning unit configured to learn a velocity and a direction for each of the ascertained topics, and learn a movement pattern by inferring a spatiotemporal correlation between the ascertained topics. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. An apparatus for detecting an abnormal movement, the apparatus comprising:
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a feature tracing unit, as executed by a processor, configured to extract features of a moving object in an input image, trace a variation in a position of the extracted features according to time, and ascertain trajectories of the extracted features; a trajectory classifying unit configured to classify the input image in units of documents indicating a bundle of the trajectories, and infer, by using an online learning method which is a probabilistic topic model, a multinomial distribution parameter probability vector value indicating histogram distribution of topics constituting each document in order to cluster positions of the trajectories for each topic in the document; a spatiotemporal correlation inferring unit configured to infer a spatiotemporal correlation on the basis of the inferred multinomial distribution parameter probability vector value; and a movement pattern online learning unit configured to learn a velocity and a direction for each of the clustered topics, and learn a movement pattern by inferring a spatiotemporal correlation between the ascertained topics. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20)
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21. A method of detecting an abnormal movement, the method comprising:
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extracting, using a processor, features of a moving object in an input image; tracing a variation in position of the extracted features according to time; ascertaining trajectories of the extracted features; classifying the input image in units of documents that are bundles of the trajectories; ascertaining probability distribution states of topics, which constitute a classified document, by using an online learning method which is a probabilistic topic model; learning a velocity and a direction for each of the ascertained topics; and learning a movement pattern by inferring a spatiotemporal correlation between the ascertained topics. - View Dependent Claims (22)
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23. A method of detecting an abnormal movement, the method comprising:
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extracting, using a processor, features of a moving object in an input image; tracing a variation in position of the extracted features according to time; ascertaining trajectories of the extracted features; classifying the input image in units of documents indicating a bundle of the trajectories; inferring, by using an online learning method which is a probabilistic topic model, a multinomial distribution parameter probability vector value indicating histogram distribution of topics constituting each document in order to cluster positions of the trajectories for each topic in the document; inferring a spatiotemporal correlation on the basis of the inferred multinomial distribution parameter probability vector value; learning a velocity and a direction for each of the clustered topics; and learning a movement pattern by inferring a spatiotemporal correlation between the ascertained topics.
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Specification