VISION BASED REAL TIME TRAFFIC MONITORING
First Claim
1. A method for detecting and tracking one or more vehicles using a system for obtaining two-dimensional visual data depicting traffic flow on a road, the two-dimensional visual data comprising a plurality of image frames, the method comprising:
- filtering the two-dimensional visual data using background subtraction to yield a foreground mask;
identifying a plurality of feature points from the foreground mask using a feature detector;
determining the plumb line projection of the feature points;
estimating three-dimensional world coordinates of the feature points using the plumb line projection of the feature points;
categorizing each of the feature points as either a stable feature or an unstable feature based on the estimated three-dimensional world coordinates of the feature points;
grouping stable features to form groups of associated stable features;
associating unstable features with groups of associated stable features to create segmented feature groups;
outputting data based on the segmented feature groups.
1 Assignment
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Accused Products
Abstract
A system and method for detecting and tracking one or more vehicles using a system for obtaining two-dimensional visual data depicting traffic flow on a road is disclosed. In one exemplary embodiment, the system and method identifies groups of features for determining traffic data. The features are classified as stable features or unstable features based on whether each feature is on the frontal face of a vehicle close to the road plane. In another exemplary embodiment, the system and method identifies vehicle base fronts as a basis for determining traffic data. In yet another exemplary embodiment, the system and method includes an automatic calibration procedure based on identifying two vanishing points
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Citations
20 Claims
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1. A method for detecting and tracking one or more vehicles using a system for obtaining two-dimensional visual data depicting traffic flow on a road, the two-dimensional visual data comprising a plurality of image frames, the method comprising:
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filtering the two-dimensional visual data using background subtraction to yield a foreground mask; identifying a plurality of feature points from the foreground mask using a feature detector; determining the plumb line projection of the feature points; estimating three-dimensional world coordinates of the feature points using the plumb line projection of the feature points; categorizing each of the feature points as either a stable feature or an unstable feature based on the estimated three-dimensional world coordinates of the feature points; grouping stable features to form groups of associated stable features; associating unstable features with groups of associated stable features to create segmented feature groups; outputting data based on the segmented feature groups. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A method for detecting and tracking one or more vehicles using a system for obtaining two-dimensional visual data depicting traffic flow on a road, the two-dimensional visual data comprising a plurality of image frames, the method comprising:
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filtering the two-dimensional visual data using background subtraction to yield a foreground mask; detecting a vehicle base front from the foreground mask; tracking the vehicle base front through the plurality of image frames; outputting data based on the tracking of the vehicle base front. - View Dependent Claims (10, 11, 12, 13, 14)
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15. A method for automatically calibrating a system for detecting and tracking one or more vehicles based on two-dimensional visual data depicting traffic flow, the two-dimensional visual data comprising a plurality of image frames, the two-dimensional visual data defining a direction of travel and a direction perpendicular to the direction of travel, the method comprising:
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detecting and tracking a vehicle based on the two-dimensional visual data to determine vehicle tracks of the vehicle; estimating a first vanishing point in the direction of travel using the vehicle tracks of the detected vehicle; estimating a second vanishing point in the direction perpendicular to the direction of travel using strong image gradients found on the detected vehicle; calibrating the system for detecting and tracking one or more vehicles based on two-dimensional visual data using the first and second vanishing points. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification