EP1062637A1 - Method for determining movement of objects in a video image sequence - Google Patents
Method for determining movement of objects in a video image sequenceInfo
- Publication number
- EP1062637A1 EP1062637A1 EP99909044A EP99909044A EP1062637A1 EP 1062637 A1 EP1062637 A1 EP 1062637A1 EP 99909044 A EP99909044 A EP 99909044A EP 99909044 A EP99909044 A EP 99909044A EP 1062637 A1 EP1062637 A1 EP 1062637A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- signals
- values
- images
- difference
- pixel
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
- G06T7/254—Analysis of motion involving subtraction of images
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
Definitions
- the present invention relates to a method for detecting the movement of moving objects in a sequence of video images.
- a simpler and faster method consists in calculating the difference image in each pixel between two consecutive images of the video sequence. This difference is generally calculated using only the luminance information.
- OF CONFIRMATION values p ⁇ ses by the luminance signal respectively of the images of order 1 and 1 + 1 Vi ⁇ L (x, y) L,. 1 (x, y) - L I (x, y) or L, (x, y) and L, -. ⁇ (x, y) represent respectively the luminance signals of the pixel of coordinates (x, y) of the images of order / and of order / - 1 Due to the noise which is induced by the electronics and the sensors of the camera, we generally apply a threshold so that the difference signal is quantified as follows
- the value of a quantized signal associated with a pixel of coordinates (x, y) is a first value (here, zero) if the difference in luminance signal is less than a threshold value and is a second value (here, 1) if the difference signal is greater than said threshold value
- the thresholds to be applied are of the order of 5% of the possible excursion of the luminance values (typically if the luminance varies between 0 and 255, the threshold will be of the order of 12)
- this process it is above all the contours of moving objects that are detected. To obtain all of the zones making up a moving object, this process requires other long steps in computing time.
- a step consists in generating first and second difference images which are then each processed in a threshold detector at two levels representative of the movens levels of positive and negative noise to which a coefficient is applied If the value of a pixel of the difference images is greater than the positive threshold value, a value one is assigned to said pixel If the value of a pixel of difference images is less than the negative threshold value, a value minus one is assigned to said pixel When the pixel value is between the two threshold values, a zero value is assigned
- I (x, y) 1 if ⁇ L (x, y)> threshold I (x, y) - 0 if -threshold> zlL (x, y)> threshold where I (x, y) represents the quantized difference signal for the coordinate pixel
- the cited document provides for the use of low pass filters for image difference values
- the sensitivity of the detection is linked to the level of the threshold used for the calculation of the difference image and therefore to the level of the camera used
- a method according to the invention consists in making the differences in the values taken respectively in each pixel determined by its coordinates (x, y) of the values of the luminance signals L 1+ ⁇ (x, y) and Lj (x, y) of two consecutive images i and i + 1. The resulting difference signal is therefore
- any signals representative of at least one characteristic of the image For example, one could use instead of luminance signals, the chrominance signals One could also use a particular combination of the chrominance signals and luminance signals
- a difference image is formed of the set of pixels taking respectively the difference values ⁇ L (x, y) which will have been quantified by quantization in n-ary signals with odd n, (nl) / 2 quantization levels for positive difference values A ⁇ , y), (nl) / 2 quantization levels for negative difference values z-vL (x, y) and one level for strictly zero values
- This filtering step will, for example, consist in canceling the quantized value I (x, y) of a pixel with coordinates (x, y) if it is between two ho ⁇ zontal pixels with coordinates (x - 1, y) and (x + 1, y) or vertical coordinates (x, Y - 1) and (x, y + 1) having quantized values different from its own From this filtered difference image, we will implement a region growth stage to segment moving objects Such a stage is for example described in a book entitled "Nision by Computers" by Hermès published by R Horand and O Monga A particular realization of this segmentation can be carried out, for example, by using a connectivity of order 4 by aggregation of the pixels which are a 1 or a - 1 To supp ⁇ mer the small regions due to the noise one can, either fix a threshold on the size of the objects that we are looking for a priori, that is, if the object has contours, impose that at least one of the pixels which composes it present on
- the method according to the invention provides a much more relevant segmentation than the conventional difference method of the state of the art.
- all of the zones making up a moving object are easily set in highlight From the point of view of calculation time, only an additional simple filtering is necessary, which is not very detrimental
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Image Analysis (AREA)
- Closed-Circuit Television Systems (AREA)
Abstract
Description
Claims
Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
FR9803641A FR2776459B1 (en) | 1998-03-19 | 1998-03-19 | METHOD FOR DETECTING MOVING OBJECTS IN A SEQUENCE OF VIDEO IMAGES |
FR9803641 | 1998-03-19 | ||
PCT/FR1999/000634 WO1999048048A1 (en) | 1998-03-19 | 1999-03-19 | Method for determining movement of objects in a video image sequence |
Publications (1)
Publication Number | Publication Date |
---|---|
EP1062637A1 true EP1062637A1 (en) | 2000-12-27 |
Family
ID=9524451
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP99909044A Withdrawn EP1062637A1 (en) | 1998-03-19 | 1999-03-19 | Method for determining movement of objects in a video image sequence |
Country Status (4)
Country | Link |
---|---|
US (1) | US6754372B1 (en) |
EP (1) | EP1062637A1 (en) |
FR (1) | FR2776459B1 (en) |
WO (1) | WO1999048048A1 (en) |
Families Citing this family (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6940998B2 (en) * | 2000-02-04 | 2005-09-06 | Cernium, Inc. | System for automated screening of security cameras |
US20060221181A1 (en) * | 2005-03-30 | 2006-10-05 | Cernium, Inc. | Video ghost detection by outline |
US7822224B2 (en) | 2005-06-22 | 2010-10-26 | Cernium Corporation | Terrain map summary elements |
US20090062002A1 (en) * | 2007-08-30 | 2009-03-05 | Bay Tek Games, Inc. | Apparatus And Method of Detecting And Tracking Objects In Amusement Games |
US8571261B2 (en) * | 2009-04-22 | 2013-10-29 | Checkvideo Llc | System and method for motion detection in a surveillance video |
DE102016207705A1 (en) * | 2016-05-04 | 2017-11-09 | Robert Bosch Gmbh | Smoke detection device, method for detecting smoke of a fire and computer program |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4937878A (en) * | 1988-08-08 | 1990-06-26 | Hughes Aircraft Company | Signal processing for autonomous acquisition of objects in cluttered background |
EP0731614B1 (en) * | 1995-03-10 | 2002-02-06 | Kabushiki Kaisha Toshiba | Video coding/decoding apparatus |
US5764803A (en) * | 1996-04-03 | 1998-06-09 | Lucent Technologies Inc. | Motion-adaptive modelling of scene content for very low bit rate model-assisted coding of video sequences |
US6188776B1 (en) * | 1996-05-21 | 2001-02-13 | Interval Research Corporation | Principle component analysis of images for the automatic location of control points |
KR100259136B1 (en) * | 1997-04-19 | 2000-06-15 | 김영환 | Motion vector detection device |
-
1998
- 1998-03-19 FR FR9803641A patent/FR2776459B1/en not_active Expired - Lifetime
-
1999
- 1999-03-19 US US09/646,473 patent/US6754372B1/en not_active Expired - Lifetime
- 1999-03-19 WO PCT/FR1999/000634 patent/WO1999048048A1/en not_active Application Discontinuation
- 1999-03-19 EP EP99909044A patent/EP1062637A1/en not_active Withdrawn
Non-Patent Citations (1)
Title |
---|
See references of WO9948048A1 * |
Also Published As
Publication number | Publication date |
---|---|
FR2776459B1 (en) | 2000-04-28 |
FR2776459A1 (en) | 1999-09-24 |
US6754372B1 (en) | 2004-06-22 |
WO1999048048A1 (en) | 1999-09-23 |
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