Method of determining parking lot occupancy from digital camera images
First Claim
1. A method of determining parking lot occupancy from digital images, the method comprising:
- obtaining a layout of a parking lot having a plurality of parking spaces;
estimating parking space volume for at least one viewing angle of at least one parking space and the probability that an observed pixel belongs to the parking space volume;
acquiring one or more image frames of the parking lot from at least one digital camera;
performing pixel classification using at least one vehicle detector on the acquired one or more image frames to determine a likelihood that a pixel corresponds to a vehicle;
computing a probability that the at least one parking space is occupied by a vehicle based on a weighted sum of the probability of vehicle pixels within the region of interest of each parking space, wherein the region of interest refers to pixels that can potentially belong to a vehicle parked in a given parking space, wherein the weighted sum comprises a weighting function which gives larger weight to pixels located towards a center of the region of interest of each parking space, the weighting function decreasing the weight of a particular pixel as a distance of the particular pixel to the center increases; and
determining parking lot vacancy via a comparison of the computed probability that the at least one parking space is occupied by a vehicle to a pre-determined threshold.
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Abstract
Described herein is a method of determining parking lot occupancy from digital images, including a set-up procedure that includes receiving a layout of a parking lot and estimating parking space volume for at least one viewing angle and the probability that an observed pixel belongs to the parking space volume. The method further includes acquiring one or more image frames of the parking lot from at least one digital camera; performing pixel classification using a vehicle detector on the acquired image frames to determine a likelihood that a pixel belongs to a vehicle; computing a probability that a parking space is occupied by a vehicle based on a spatially varying membership probability density function and a likelihood of vehicle pixels within a region of interest; and determining parking lot vacancy via a comparison of the computed probability that a parking space is occupied by a vehicle to a pre-determined threshold.
37 Citations
22 Claims
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1. A method of determining parking lot occupancy from digital images, the method comprising:
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obtaining a layout of a parking lot having a plurality of parking spaces; estimating parking space volume for at least one viewing angle of at least one parking space and the probability that an observed pixel belongs to the parking space volume; acquiring one or more image frames of the parking lot from at least one digital camera; performing pixel classification using at least one vehicle detector on the acquired one or more image frames to determine a likelihood that a pixel corresponds to a vehicle; computing a probability that the at least one parking space is occupied by a vehicle based on a weighted sum of the probability of vehicle pixels within the region of interest of each parking space, wherein the region of interest refers to pixels that can potentially belong to a vehicle parked in a given parking space, wherein the weighted sum comprises a weighting function which gives larger weight to pixels located towards a center of the region of interest of each parking space, the weighting function decreasing the weight of a particular pixel as a distance of the particular pixel to the center increases; and determining parking lot vacancy via a comparison of the computed probability that the at least one parking space is occupied by a vehicle to a pre-determined threshold. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A system for determining parking lot occupancy from digital images, the system comprising:
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a database that stores digital images and data related to digital image processing, wherein the data includes one or more parking lot layouts; and an image processing unit that includes a processor, a system memory, and a system bus that couples the system memory to the processing unit, wherein the image processing unit is operative to; obtain a layout of a parking lot having a plurality of parking spaces; estimate parking space volume for at least one viewing angle of at least one parking space and the probability that an observed pixel belongs to the parking space volume; acquire one or more image frames of the parking lot from at least one digital camera; perform pixel classification using at least one vehicle detector on the acquired one or more image frames to determine a likelihood that a pixel belongs to a vehicle; compute a probability that the at least one parking space is occupied by a vehicle based on a weighted sum of the probability of vehicle pixels within the region of interest of each parking space, wherein the region of interest refers to pixels that can potentially belong to a vehicle parked in a given parking space, wherein the weighted sum comprises a weighting function which gives larger weight to pixels located towards a center of the region of interest of each parking space, the weighting function decreasing the weight of a particular pixel as a distance of the particular pixel to the center increases; and determine parking lot vacancy via a comparison of the computed probability that the at least one parking space is occupied by a vehicle to a pre-determined threshold. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17)
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18. A method of determining parking lot occupancy from digital images, the method comprising:
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obtaining a layout of a parking lot having a plurality of parking spaces; estimating parking space volume for at least one viewing angle of at least one parking space and the probability that an observed pixel belongs to the parking space volume; acquiring one or more image frames of the parking lot from at least one digital camera; performing pixel classification using at least one vehicle detector on the acquired one or more image frames to determine a likelihood that a pixel corresponds to a vehicle, wherein the pixel classification is performed using at least one of a support vector machine (SVM) classifier that uses rotation-invariant local binary patterns (LBPs) as input features and a TextonBoost classifier; computing a probability that the at least one parking space is occupied by a vehicle based on a spatially varying membership probability density function and a likelihood of vehicle pixels within a region of interest; using one of a first model and a second model to determine a probability of pixel x being a vehicle, wherein the first model uses a soft output of the TextonBoost classifier and a hard output of the SVM classifier and the second model uses a hard output of the TextonBoost classifier and a hard output of the SVM classifier, wherein the first model comprises;
Pv(x)=η
xPvTB(x)+(1−
η
x)PvLBPwhere PvTB(x)ε
[0,1] is the soft probability of a pixel corresponding to a vehicle, given by the TextonBoost classifier, and PvLBP(x)ε
{0,1} is the hard classification of a pixel corresponding to a vehicle, given by the SVM classifier with LBP values as inputs, andwherein the second model comprises one of;
Pv(x)=max(PvTB(x),PvLBP) or Pv(x)=min(PvTB(x),PvLBP)where PvTB(x)ε
{0,1} is the hard classification of a pixel corresponding to a vehicle, given by the TextonBoost classifier, and PvLBP(x)ε
{0,1} is the hard classification of a pixel corresponding to a vehicle, given by the SVM classifier with LBPs as inputs; anddetermining parking lot vacancy via a comparison of the computed probability that the at least one parking space is occupied by a vehicle to a pre-determined threshold. - View Dependent Claims (19, 20, 21, 22)
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Specification