One-shot high-accuracy geometric modeling of three-dimensional scenes

Abstract

A method for providing three-dimensional (3-D) digitization of a scene with increased accuracy, speed and detail detection establishing a bijective association of distinguishable plurality of strips projected onto a 3-D scene.

A 3-D imaging system obtaining frames of 3-D measurements by projecting polygonal formation of linear strips with unrestricted relative motion providing substantially denser sampling of 3-D scene.

Claims

1. A method of obtaining three-dimensional (3D) coordinates of physical scenes comprising steps of: (a) illuminating the a scene by at least one radiation pattern emanating from a projector frame, having a predetermined number of interconnected rectilinear distinguishable strips having non-regular and non-overlapping reticular configuration having distinguishable two-dimensional (2D) pixel formation at connecting vertices positioned at predetermined coordinates; (b) recording at least a portion of said rectilinear strip configured in said polygonal formations in at least one digital frame in the form of profiles of illuminated pixels corresponding to said at least a portion of said rectilinear strips; (c) locating said at least a portion of said polygonal formations in at least said digital frame; (d) identifying at least a subset of said distinguishable 2D pixel formations at said connecting vertices in said at least one digital frame, to corresponding vertices in said radiation pattern, and (e) identifying at least a subset of said illuminated profiles of pixels in said at least one digital frame to corresponding said interconnected rectilinear distinguishable strips in said radiation pattern; (f) calculating 3D coordinates corresponding by triangulating said illuminated pixels in said subset of profiles in said digital frame and said identified subset of said interconnected strips in said radiation pattern with sub pixel precision.

2. A digitization system comprising: (a) at least one projection assembly configured to emanate at least one radiation pattern onto a scene, wherein said pattern comprises a predetermined number of interconnected rectilinear distinguishable strips, wherein said strips have non-regular non-overlapping reticular configuration, wherein said strips have distinguishable two-dimensional (2D) pixel formations at connecting vertices, wherein said connecting vertices have predetermined coordinates; (b) at least one image capture assembly configured to capture radiation reflected from said scene in at least one digital frame, wherein said digital frame comprises at least some of said rectilinear distinguishable strips and connecting vertices in form of profiles of illuminated pixels and some of said connecting vertices in form of illuminated pixel groupings; (c) at least one computing unit configured to: (i) determine location at least a subset of said profiles of illuminated pixels and said illuminated pixel groupings; (ii) identify at least a subset of said illuminated pixel grouping in said digital frame by corresponding connecting vertices in radiation pattern; (iii) identify at least a subset of said at least some of said profiles in said at least one digital frame by corresponding said strips in said radiation pattern; (iv) calculate 3D coordinates of said at least a subset of said profiles in said at least one digital frame with sub pixel precision.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0043] With specific reference to the drawings the particulars are described to provide useful and readily understanding of principles and conceptual aspects of present invention, such that taken with the description is making apparent to those skilled in the art how the invention may be embodied into practice.

[0044] FIG. 1 is a schematic diagram illustrating one embodiment of the present invention showing how bi-dimensional light pattern is utilized together with various means to obtain three-dimensional coordinates of imaged object.

[0045] FIG. 2 is a simplified depiction illustrating reference images formation and schematic representation of reflected pattern in accordance to embodiments of present invention.

[0046] FIG. 3 is a representation of bi-dimensional pattern and bi-dimensional pattern reflection from a 3-D object depicting identification of two-dimensional nodes on a reference pattern image in accordance to epipolar principles.

[0047] FIG. 4 contains simplified representation of bi-dimensional pattern having some transparent lattice loops in accordance to epipolar depth.

DETAILED DESCRIPTION

[0048] FIG. 1 is a simplified representation of the principle of the preferred embodiment of present invention. In particular the system 10 comprises projector 102, image sensor 106 and computation means 107. Projector 102 emits electromagnetic radiation represented by ray 104. A bi-dimensional pattern 101 comprising a lattice of rectilinear segments forming irregular polygonal eyelets, is projected onto three-dimensional object 100. The pattern 101 is in the form of at least one transparency or in the form of at least one diffractive optical element (DOE) configured in accordance to projector 102. Electromagnetic radiation is generated by at least one pattern projector 110 illuminating pattern 101. Projector 110 could be in the form of surface-emitting laser arrays (VCSEL), resonant cavity light emitting diode arrays (RC-LED) or wavelength limited LED.

[0049] Radiation 104 illuminates at least a portion of object 100 under computer 107 control and electronic coupling 103. At least a portion of the radiation reflected form object 100 is recorded by image sensor 106 under computer 107 control and stored in digital frame 105 in the form of curvilinear formations of high-intensity pixels.

[0050] Pixels in the frame 105 are detected and analyzed by computer 107 utilizing imaging processing means to identify respective rectilinear segments in projected bi-dimensional pattern 101 corresponding to curvilinear formations. Computer 107 outputs 3D coordinates of illuminated object 100 by triangulating corresponding bi-dimensional pattern rectilinear segments and imaged curvilinear segments localized in digital frame 105.

[0051] In some embodiments projector 102 comprise multiple laser arrays elements are combined to illuminate certain portions of pattern 101 in different portions of the scene or project sequences of shifted versions to enable higher scene sampling.

[0052] FIG. 2 is a schematic representation of image formation of the object 200 encoded by projection of pattern 206 by projector 201, having a depth of field 210, and recorded by image sensor 202 in digital frame 208.

[0053] Digital image recorded at digital frame 208 can be construed as combining virtual light sections effected by pattern 206 on object 200, when observed from perspective of image sensor 202. For example, rays reflected by perspective transformed pattern at section plane Pa, inside range 210, correspond to a first sub-set of pixels in frame 208 and belong to a sub-set of curvilinear segments in frame 208. Consequently, the depth of contributed pixels have the depth of Pa.

[0054] Section plane Pb, at an adjacent predetermined distance from Pa, correspond to a second sub-set of pixels in 208 distinct from subset contributed by Pa and also lie on a subset curvilinear segments in frame 208.

The first and second sub-set of pixels are pinpointed by correlating image in frame 208 to back-projected versions of the pattern in Pa and Pb positions in camera 202 frame.
To distinguish the pixels that belong to Pa and Pb depths, correlation is conducted step-wise across entire depth of field 210. Because polygonal structure is pseudo-random, pixels at Pa depth and pixels at Pb depth lay on same curvilinear segment in frame 208. For example at least some of pixels representing consecutive depths in range 205 can belong to curvilinear segment 207.

[0055] Because of pseudo-random polygonal structure other curvilinear segments may correlate to calculated pattern. However, only consecutive correlations on same curvilinear segment are validated and assigned depth at each pixel position.

[0056] In at least one embodiment, polygonal vertices are identified in projected bi-dimensional pattern by correlating pixels in frame 208 to versions of perspective transformed pattern in 210 reprojected to image sensor 202 viewpoint. The correlation is carried out over a subset of perspective transformed patterns having polygonal vertices on corresponding epipolar line. For example, to identify polygonal vertex 209 incremental correlation is carried out on perspective transformed patterns that include polygonal vertex on epipolar line corresponding to vertex 209.

[0057] FIG. 3 depicts schematically the process of vertices identification in imaged object 302. Search is confined to region 303 corresponding to imaged object region 304. Magnified versions of region 304 and 303 are represented in 310 and 306 respectively. A search window of predetermined size 308 is centered around a vertex having corresponding epipolar line 311 in 306. Correlation of window 308 is advantageously conducted at vertices positions in 306 that belong to epipolar line 311. Similarly, window 309, centered around another vertex in 310 and having a corresponding epipolar line 312, is identified by correlation to window 307 in 306, carried out at vertices laying on 312, utilizing the process from FIG. 2.

[0058] It will be apparent for the skilled in the art that multiple vertices are identified inside each window 308, 309. It will also be apparent for the skilled in the art that correlation windows may overlap such that at least a subset of vertices are identified multiple times. Validation is carried out by results consistency at overlapping location.

[0059] One advantage of the method of current invention is ability to determine local surface orientation at each vertex because distinguishable curvilinear segments around the vertex and identified lattice linear segments give rise to intersecting three-dimensional planes, where intersecting line segment are tangent at the vertex.

[0060] It is in the spirit of this invention that correlation computation for the purpose of vertices identification can be substituted by other techniques known in the art such as neural network search techniques, and are therefore part of this invention.

[0061] In another embodiment vertices identification is sped up utilizing a modified bi-dimensional pattern 400, schematically represented in FIG. 4, having a predetermined number of polygons transparent to projected radiations, where at least a portion of transparent polygons appear in digital frame 208 as distinctive filled regions. Pattern 400 is designed such that epipolar lines share a minimal number of filled polygons. That way correlation is carried out at a smaller number of locations on respective epipolar lines, as such reducing the number of computations necessary to identify vertices of filled polygonal eyelets. Moreover, identification of neighboring vertices is also simplified because a smaller number of epipolar locations need to be correlated. Those skilled in the art will realize that the size of search neighborhood around filled polygonal eyelets is dependent of epipolar travel and therefore dependent of geometry of the setup.