WO2009124663A1 - Recherche de correspondances semi-globale dans des images stéréo - Google Patents

Recherche de correspondances semi-globale dans des images stéréo Download PDF

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Publication number
WO2009124663A1
WO2009124663A1 PCT/EP2009/002228 EP2009002228W WO2009124663A1 WO 2009124663 A1 WO2009124663 A1 WO 2009124663A1 EP 2009002228 W EP2009002228 W EP 2009002228W WO 2009124663 A1 WO2009124663 A1 WO 2009124663A1
Authority
WO
WIPO (PCT)
Prior art keywords
image
costs
pixel
accumulated
dimensional paths
Prior art date
Application number
PCT/EP2009/002228
Other languages
German (de)
English (en)
Inventor
Stefan Hahn
Original Assignee
Daimler Ag
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Daimler Ag filed Critical Daimler Ag
Publication of WO2009124663A1 publication Critical patent/WO2009124663A1/fr

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
    • G01C11/02—Picture taking arrangements specially adapted for photogrammetry or photographic surveying, e.g. controlling overlapping of pictures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G06T7/55—Depth or shape recovery from multiple images
    • G06T7/593—Depth or shape recovery from multiple images from stereo images
    • G06T7/596—Depth or shape recovery from multiple images from stereo images from three or more stereo 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
    • G06V10/24—Aligning, centring, orientation detection or correction of the image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10004—Still image; Photographic image
    • G06T2207/10012—Stereo images
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20021—Dividing image into blocks, subimages or windows

Definitions

  • the invention relates to a method for determining correspondences of pixels in at least two stereoscopically recorded images according to the preamble of claim 1.
  • the invention is therefore based on the object to provide an improved method for determining correspondences of pixels in stereoscopically recorded images, in which a memory requirement is reduced.
  • a calculation of costs of dissimilarity is performed for each pixel of one of the images based on intensities of the pixel and a pixel of the other image regarded as potentially corresponding. Along a number of one-dimensional paths that flow into the pixel, the costs are accumulated. From the pixels of the other image considered as potentially corresponding, the one to create a disparity map is selected in which a global energy is at least minimizing the cost of dissimilarity.
  • the image for determining the correspondences is subdivided into image sections of size (n + 1) x (m + 1) in an inventive manner.
  • not all accumulated costs are stored, as is conventional in the art, but only the costs accumulated in each of the one-dimensional paths for every nth row and every mth column of the picture.
  • the storage takes place for example in an external memory, while the calculation for example, in an FPGA.
  • one of the image sections is loaded in each case.
  • the stored accumulated costs which relate to an edge of the image section are loaded.
  • the costs accumulated in each of the one-dimensional paths for an interior of the image section are recalculated.
  • the computation outlay increases by about a factor of 2, but the external memory bandwidth can be reduced by at least the factor m / 2 to factor m, so that less memory is required.
  • the external memory bandwidth can be reduced by at least the factor m / 2 to factor m, so that less memory is required.
  • both the cost of the memory itself and the power consumption of the memory are reduced.
  • the prerequisite is that an internal memory of a microprocessor or an FPGA, in which the calculation is performed, is sufficiently large for the calculation of all one-dimensional paths for the selected size of the image section. If necessary, adjust the size of the image section.
  • Fig. 1 is a schematic representation of an image with a pixel and eight one-dimensional paths that open in the pixel, and
  • Fig. 2 is a diagram of a disparity of a pixel in dependence on a direction of the one-dimensional path.
  • the figure shows a picture 1 and a pixel p.
  • the other image 1 'and the pixel p' regarded as potentially corresponding are not shown.
  • the method is used to determine correspondences of pixels (pixels p, p ') in at least two stereoscopically recorded images 1, 1'.
  • the cost of disparity is the cost of matching p to d.
  • the one for creating a disparity map D (p) is selected in which a global energy is at least comprising the cost C (p, d) of dissimilarity.
  • the global energy can too Strafterme Pl, P2 are included, which take into account the changes of adjacent disparities to each other, as is clear from Figure 2 and as shown in the following formula:
  • a small penalty term pl in the determination of global energy is taken into account when the disparity d between adjacent pixels p, p 'varies slightly and a large penalty term p2, when an abrupt change of the disparity d between adjacent pixels p, p 1 is present. This is also called a smoothness constraint.
  • the image 1 is subdivided into image sections of size (n + l) x (m + l) in order to determine the correspondences.
  • the costs S (p, d) accumulated in each of the one-dimensional paths L for every nth row and every mth column of the picture 1 are stored in an accumulated cost matrix, the complexity of the algorithm relating to the Time 0 (WHD) is (WHD - width, height, disparity rank, width, height, disparity range).
  • the storage takes place, for example, in an external memory, while the calculation takes place, for example, in an FPGA or a microcontroller. Subsequently, one of the image sections is loaded in each case. In this case, the stored accumulated costs S (p, d) which relate to an edge of the image section are loaded. The costs S (p, d) accumulated in each of the one-dimensional paths L for an interior of the image section are recalculated.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Image Processing (AREA)

Abstract

L'invention concerne un procédé destiné à déterminer des correspondances de points d'image (p, p' ) dans au moins deux images (1, 1') acquises de manière stéréoscopique. Selon ce procédé, dans chaque pixel (p) de l'une des images (1), un calcul des coûts (C(p,d)) d'une dissimilarité est effectué à l'aide de l'intensité du pixel (p) et de l'intensité d'un pixel (p') considéré comme un pixel potentiellement correspondant de l'autre image (1'). Le long d'un certain nombre de chemins unidimensionnels (L) qui mènent au pixel (p), un cumul des coûts (C(p,d) ) est réalisé. Pour créer une carte de disparités (D(p)), on sélectionne, parmi les pixels (p') considérés comme pixels potentiellement correspondants de l'autre image (1'), le pixel (p') pour lequel une énergie globale comprenant au moins les coûts (C(p,d)) de la dissimilarité est minimale. L'image (1) destinée à déterminer les correspondances dans des parties d'image de grandeur (n+1)x(n+1) est sous-divisée. Les coûts cumulés (S(p,d)) sont mémorisés dans chacun des chemins unidimensionnels (L) pour chaque nième rangée et pour chaque mième colonne. Une des parties d'image est chargée à chaque fois. Les coûts cumulés (S(p,d)) mémorisés pour un bord de ladite partie d'image sont également chargés, et les coûts cumulés (S(p,d) dans chaque chemin unidimensionnel (L) sont recalculés pour l'intérieur de ladite partie d'image.
PCT/EP2009/002228 2008-04-08 2009-03-26 Recherche de correspondances semi-globale dans des images stéréo WO2009124663A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102008017834.9 2008-04-08
DE102008017834A DE102008017834A1 (de) 2008-04-08 2008-04-08 Verfahren zur Bildverarbeitung von Stereobildern

Publications (1)

Publication Number Publication Date
WO2009124663A1 true WO2009124663A1 (fr) 2009-10-15

Family

ID=39777746

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2009/002228 WO2009124663A1 (fr) 2008-04-08 2009-03-26 Recherche de correspondances semi-globale dans des images stéréo

Country Status (2)

Country Link
DE (1) DE102008017834A1 (fr)
WO (1) WO2009124663A1 (fr)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102008046505B4 (de) 2008-09-09 2023-06-29 Mercedes-Benz Group AG Verfahren zur Bildverarbeitung von Stereobildern
DE102009012441B4 (de) 2009-03-12 2010-12-09 Deutsches Zentrum für Luft- und Raumfahrt e.V. Verfahren zur Reduktion des Speicherbedarfs bei der Bestimmung von Disparitätswerten für mindestens zwei stereoskopisch aufgenommene Bilder
DE102009052868A1 (de) 2009-11-13 2010-06-17 Daimler Ag Verfahren zum Betrieb eines Fahrassistenzsystems eines Fahrzeugs
DE102013014314A1 (de) 2013-08-29 2014-03-06 Daimler Ag Verfahren zur Ermittlung von Disparitätskarten

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
HEIKO HIRSCHMULLER ET AL: "Evaluation of Cost Functions for Stereo Matching", COMPUTER VISION AND PATTERN RECOGNITION, 2007. CVPR '07. IEEE CONFERENCE ON, IEEE, PISCATAWAY, NJ, USA, 1 June 2007 (2007-06-01), pages 1 - 8, XP031114505, ISBN: 978-1-4244-1179-5 *
HEIKO HIRSCHMULLER: "Stereo Processing by Semiglobal Matching and Mutual Information", IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, IEEE SERVICE CENTER, LOS ALAMITOS, CA, US, vol. 30, no. 2, 1 February 2008 (2008-02-01), pages 328 - 341, XP011195575, ISSN: 0162-8828 *
HIRSCHMULLER H ED - GANG PAN ET AL: "Accurate and Efficient Stereo Processing by Semi-Global Matching and Mutual Information", COMPUTER VISION AND PATTERN RECOGNITION, 2005 IEEE COMPUTER SOCIETY CONFERENCE ON, IEEE, PISCATAWAY, NJ, USA, vol. 2, 20 June 2005 (2005-06-20), pages 807 - 814, XP010817537, ISBN: 978-0-7695-2372-9 *

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