US6985172B1
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Model-based incident detection system with motion classification
Assignee: Southwest Research Institute
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Filing: 2002-01-25
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Granted: 2006-01-10
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Expires: 2022-01-25
Abstract
Abstract Surveillance apparatus and methods effective for detecting incidents are based upon improved image processing techniques applied to infrared and visible light spectrum images in a time sequence. A reference image is generated by removing motion objects from an image of a region of interest. The reference image is compared to an image to be analyzed to detect motion. Detected motion is analyzed and classified as motion objects. The motion objects are then compared to a motion model, which classifies the objects as being anticipated or unanticipated.
Inventors
- 👤 Michael P. Rigney
- 👤 Michael J. Magee
- 👤 Ernest A. Franke
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 12:13
CPC Classifications
G; G08; G08B; G08B13/00; G08B13/18; G08B13/189; G08B13/194; G08B13/196; G08B13/19602; G06; G06T; G06T7/00; G06T7/20; G06T7/246; G06T7/254; G06V; G06V20/00; G06V20/50; G06V20/52; G06V20/54; G06V40/00; G06V40/20; G08B13/19604; G08B13/19606; G08B13/19613; G08B13/19678; G08B13/19691; G06T2207/00; G06T2207/30; G06T2207/30241
Claims Analysis
Total Claims: 17
Claim 1
Independent Claim
176 words
A method of using video images to monitor incidents in a region of interest, comprising the steps of: computing a reference image from a set of images by removing moving objects from the set of images; storing a motion model representing anticipated motion in the region of interest; acquiring a image to be analyzed; computing a temporal difference image by comparing the image to be analyzed with the reference image; repeating the step of computing a temporal difference image to obtain a set of temporal difference images; calculating, from the set of temporal difference images, at least one temporal difference statistic for each pixel; detecting motion in a temporal difference image by separating motion pixels from background in the temporal difference image, using the temporal difference statistic; grouping motion pixels into motion objects; extracting features from the objects; comparing the features of motion objects to the motion model; wherein the motion model classifies objects as anticipated or not anticipated; and wherein the motion model further classifies anticipated objects as being of interest or not of interest.
Claim 2
Independent Claim
176 words
A method of using video images to monitor incidents in a region of interest, comprising the steps of: computing a reference image from a set of images by removing moving objects from the set of images; storing a motion model representing anticipated motion in the region of interest; acquiring a image to be analyzed; computing a temporal difference image by comparing the image to be analyzed with the reference image; repeating the step of computing a temporal difference image to obtain a set of temporal difference images; calculating, from the set of temporal difference images, at least one temporal difference statistic for each pixel; detecting motion in a temporal difference image by separating motion pixels from background in the temporal difference image, using the temporal difference statistic; grouping motion pixels into motion objects; extracting features from the objects; comparing the features of motion objects to the motion model; wherein the motion model classifies objects as anticipated or not anticipated; and wherein the motion model further classifies anticipated objects as being of interest or not of interest.
Claim 3
Dependent Claim
70 words
The method of claim 1 , wherein the step of computing a reference image is performed by calculating a median pixel value for each pixel in an image sequence, the image sequence comprising at least a first image and a second image, and by removing moving objects from the image sequence by replacing each pixel value in at least one image of the image sequence with the median pixel value.
Claim 4
Dependent Claim
70 words
The method of claim 1 , wherein the step of computing a reference image is performed by determining a minimum pixel value for each pixel in an image sequence, the image sequence comprising at least a first image and a second image, and by removing moving objects from the image sequence by replacing each pixel value in at least one image of the image sequence with the minimum pixel value.
Claim 5
Dependent Claim
70 words
The method of claim 1 , wherein the step of computing a reference image is performed by determining a maximum pixel value for each pixel in an image sequence, the image sequence comprising at least a first image and a second image, and by removing moving objects from the image sequence by replacing each pixel value in at least one image of the image sequence with the maximum pixel value.
Claim 6
Dependent Claim
34 words
The method of claim 1 , wherein the step of computing a temporal difference image is performed by subtracting pixel values in the image to be analyzed from pixel values of the reference image.
Claim 7
Dependent Claim
34 words
The method of claim 1 , wherein the step of computing a temporal difference image is performed by subtracting pixel values in the reference image from pixel values of the image to be analyzed.
Claim 8
Dependent Claim
41 words
The method of claim 1 , wherein the step of computing a temporal difference image is performed by calculating the absolute value of the difference between pixel values in the image to be analyzed and pixel values of the reference image.
Claim 9
Dependent Claim
16 words
The method of claim 1 , wherein the temporal difference statistic is an nth percentile statistic.
Claim 10
Dependent Claim
15 words
The method of claim 1 , wherein the temporal difference statistic is a mean statistic.
Claim 11
Dependent Claim
16 words
The method of claim 1 , wherein the temporal difference statistic is a standard deviation statistic.
Claim 12
Dependent Claim
39 words
The method of claim 1 , wherein the step of detecting motion is performed by using the temporal difference statistic of each pixel to determine a threshold and by comparing the temporal difference image with the threshold pixel values.
Claim 13
Dependent Claim
16 words
The method of claim 11 , wherein the threshold is based on an nth percentile statistic.
Claim 14
Dependent Claim
16 words
The method of claim 11 , wherein the threshold is based on a standard deviation statistic.
Claim 15
Dependent Claim
16 words
The method of claim 1 , wherein the classifying step is performed by extracting spatial features.
Claim 16
Dependent Claim
16 words
The method of claim 1 , wherein the classifying step is performed by extracting temporal features.
Claim 17
Dependent Claim
21 words
The method of claim 1 , further comprising the step of generating a response signal in response to the classifying step.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2009-01-09 | 2009-07-11 | 2010-01-10 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2013-01-09 | 2013-07-11 | 2014-01-10 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2017-01-09 | 2017-07-11 | 2018-01-10 | $7700.00 | Window Closed / Lapsed |