US7224852B2
Expired / Lapsed
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Video segmentation using statistical pixel modeling
Assignee: Motorola Solutions Inc
•
Filing: 2003-09-22
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Granted: 2007-05-29
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Expires: 2023-09-22
Abstract
Abstract A method for segmenting video data into foreground and background portions utilizes statistical modeling of the pixels. A statistical model of the background is built for each pixel, and each pixel in an incoming video frame is compared with the background statistical model for that pixel. Pixels are determined to be foreground or background based on the comparisons. The method for segmenting video data may be further incorporated into a method for implementing an intelligent video surveillance system.
Inventors
- 👤 Alan J. Lipton
- 👤 Mark C. Allmen
- 👤 Niels Haering
- 👤 William E. Severson
- 👤 Thomas M. Strat
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 11:40
CPC Classifications
G; G08; G08B; G08B13/00; G08B13/18; G08B13/189; G08B13/194; G08B13/196; G06; G06T; G06T7/00; G06T7/10; G06T7/11; G06T7/143; G06T7/194; G06T7/20; G06T7/277; G06V; G06V10/00; G06V10/20; G06V10/26; G06V10/28; G06V20/00; G06V20/50; G06V20/52; G08B31/00; G06T2207/00; G06T2207/10; G06T2207/10016; G06T2207/30; G06T2207/30241; G06V2201/00; G06V2201/01
Claims Analysis
Total Claims: 7
Claim 1
Independent Claim
109 words
A method of implementing an intelligent video surveillance system, comprising: obtaining a frame sequence from an input video stream; executing a first-pass method for each frame of the frame sequence, the first-pass method comprising the steps of: aligning the frame with a scene model; and updating a background statistical model; finalizing the background statistical model; executing a second-pass method for each frame of the frame sequence, the second-pass method comprising the steps of: labeling each region of the frame; and performing spatial/temporal filtering of the regions of the frame; identifying and classifying objects using the labeled and filtered regions; and analyzing behaviors of at least one of the objects.
Claim 2
Independent Claim
109 words
A method of implementing an intelligent video surveillance system, comprising: obtaining a frame sequence from an input video stream; executing a first-pass method for each frame of the frame sequence, the first-pass method comprising the steps of: aligning the frame with a scene model; and updating a background statistical model; finalizing the background statistical model; executing a second-pass method for each frame of the frame sequence, the second-pass method comprising the steps of: labeling each region of the frame; and performing spatial/temporal filtering of the regions of the frame; identifying and classifying objects using the labeled and filtered regions; and analyzing behaviors of at least one of the objects.
Claim 3
Dependent Claim
12 words
A computer-readable medium comprising software implementing the method of claim 1 .
Claim 4
Dependent Claim
21 words
An intelligent video surveillance system comprising a computer system comprising: a computer; and a computer-readable medium according to claim 2 .
Claim 5
Independent Claim
72 words
A method of implementing an intelligent video surveillance system, comprising: obtaining a frame sequence from a video stream; for each frame in the frame sequence, performing the following steps: aligning the frame with a scene model; building a background statistical model; labeling the regions of the frame; and performing spatial/temporal filtering; identifying and classifying objects based on the results of the labeling and filtering; and analyzing behaviors of at least one object.
Claim 6
Independent Claim
72 words
A method of implementing an intelligent video surveillance system, comprising: obtaining a frame sequence from a video stream; for each frame in the frame sequence, performing the following steps: aligning the frame with a scene model; building a background statistical model; labeling the regions of the frame; and performing spatial/temporal filtering; identifying and classifying objects based on the results of the labeling and filtering; and analyzing behaviors of at least one object.
Claim 7
Dependent Claim
12 words
A computer-readable medium comprising software implementing the method of claim 4 .
References Cited (Backward Citations)
US4764971A
Cited
US4949389A
Cited
US5448651A
Cited
US5048095A
Cited
US5519789A
Cited
US5586200A
Cited
US5671294A
Cited
US5724456A
Cited
US5802203A
Cited
US5696551A
Cited
US5768413A
Cited
US6049363A
Cited
US6078619A
Cited
US5875305A
Cited
US6337917B1
Cited
US6008865A
Cited
US5764306A
Cited
US6249613B1
Cited
US6195458B1
Cited
US6396876B1
Cited
US6058210A
Cited
US5990955A
Cited
US6349113B1
Cited
US6393054B1
Cited
US6278466B1
Cited
US6404925B1
Cited
US20020063154A1
Cited
US20050169367A1
Cited
US6625310B2
Cited
US20040151374A1
Cited
US6987451B2
Cited
US20040240546A1
Cited
US20060066722A1
Cited
USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2010-05-28 | 2010-11-27 | 2011-05-29 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2014-05-28 | 2014-11-27 | 2015-05-29 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2018-05-28 | 2018-11-27 | 2019-05-29 | $7700.00 | Window Closed / Lapsed |