CN109410277B - Virtual mark point filtering method and system - Google Patents

Virtual mark point filtering method and system Download PDF

Info

Publication number
CN109410277B
CN109410277B CN201811360233.7A CN201811360233A CN109410277B CN 109410277 B CN109410277 B CN 109410277B CN 201811360233 A CN201811360233 A CN 201811360233A CN 109410277 B CN109410277 B CN 109410277B
Authority
CN
China
Prior art keywords
tracking
mark points
numerical values
mark
distances
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.)
Active
Application number
CN201811360233.7A
Other languages
Chinese (zh)
Other versions
CN109410277A (en
Inventor
邓小武
蔡博凡
蓝培钦
康德华
彭应林
王彬
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Klarity Medical & Equipment Gz Co ltd
Original Assignee
Klarity Medical & Equipment Gz Co ltd
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 Klarity Medical & Equipment Gz Co ltd filed Critical Klarity Medical & Equipment Gz Co ltd
Priority to CN201811360233.7A priority Critical patent/CN109410277B/en
Publication of CN109410277A publication Critical patent/CN109410277A/en
Application granted granted Critical
Publication of CN109410277B publication Critical patent/CN109410277B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B90/00—Instruments, implements or accessories specially adapted for surgery or diagnosis and not covered by any of the groups A61B1/00 - A61B50/00, e.g. for luxation treatment or for protecting wound edges
    • A61B90/36—Image-producing devices or illumination devices not otherwise provided for
    • A61B90/37—Surgical systems with images on a monitor during operation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Surgery (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Medical Informatics (AREA)
  • Pathology (AREA)
  • Multimedia (AREA)
  • Radiology & Medical Imaging (AREA)
  • Biomedical Technology (AREA)
  • Gynecology & Obstetrics (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • Molecular Biology (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
  • Image Analysis (AREA)
  • Length Measuring Devices By Optical Means (AREA)

Abstract

The invention discloses a method and a system for filtering virtual mark points, wherein the method comprises the following steps: step S1, acquiring the coordinates of k real mark points on the tracked object, randomly selecting one real mark point, calculating the distance between the real mark point and other mark points, and acquiring k-1 numerical values; step S2, tracking the mark points on the tracked object by using the mark point tracking device, acquiring the data of m tracking mark points acquired by the mark point tracking device, and acquiring the coordinates of the m tracking mark points; step S3, sequentially calculating the distance between each tracking mark point and the rest tracking mark points, wherein m tracking mark points obtain m groups of distances, and each group of distances has m-1 numerical values; and step S4, traversing m groups of distances of the m tracking mark points, matching m-1 numerical values with the k-1 numerical values obtained in the step S1 in sequence, and realizing virtual mark point filtering according to a matching result.

Description

Virtual mark point filtering method and system
Technical Field
The invention relates to the technical field of position accurate measurement, in particular to a virtual mark point filtering method and system.
Background
Currently, binocular vision cameras have been widely used in application studies, such as surgical operations for performing image-guided procedures, such as neurosurgery, orthopedics, or radiotherapy.
As shown in fig. 1, the main system components of the binocular vision camera are a Position Sensor (Position Sensor) and an illuminator (illuminators), infrared light (IR light) is emitted from the illuminator (illuminators) and reflected by the mark points to the Position Sensor, thereby measuring the 3D spatial Position and transformation information of the mark points.
The binocular vision camera establishes a coordinate system at a Position Sensor (Position Sensor), and the origin and coordinate axes are shown in fig. 2. This coordinate system is well defined by NDI corporation and does not allow for modification. When optical measurement is carried out, the spatial position of the mark point in the measurement range is calculated by using the coordinate system as an origin.
In order to determine the position of the marker point, it is assumed that the position sensor emits a virtual line from each sensor to the image measurement center of the marker point, as shown in fig. 3, and the point where two virtual lines intersect, i.e., the position of the marker point. The system considers that this point is likely to be a marker point by calculating the distance between the crossing lines if the distance is less than a predefined limit value. Otherwise, this point is discarded, and this distance is called line separation.
In a special case, if two or two markers exist on the same plane, the virtual lines emitted from the sensor intersect more than one place, and the line distance is just within a predefined limit, so that more markers are recognized than the real markers exist, and the multiple recognized markers are called virtual markers (phantom markers), as shown in fig. 4. The more markers that are coplanar, the more virtual markers. Assuming n coplanar markers, at most n x (n-1) virtual markers are generated. The virtual mark points refer to a plurality of solutions obtained by mathematical operation due to coplanar arrangement of real mark points.
That is to say, when the binocular vision camera identifies coplanar mark points, the identified mark points are more than the mark points actually existing due to the defects of the self-measurement technology and the calculation method, that is, virtual mark points appear. Therefore, it is necessary to provide a technical means to implement the filtering of the virtual mark points to solve the above problems.
Disclosure of Invention
In order to overcome the defects of the prior art, the present invention provides a method and a system for filtering virtual mark points, so as to achieve the purpose of filtering the virtual mark points generated by the coplanar mark points.
In order to achieve the above object, the present invention provides a method for filtering virtual mark points, comprising the following steps:
step S1, acquiring the coordinates of k real mark points on the tracked object, randomly selecting one real mark point, calculating the distance between the real mark point and other mark points, and acquiring k-1 numerical values;
step S2, tracking the mark points on the tracked object by using the mark point tracking device, acquiring the data of m tracking mark points acquired by the mark point tracking device, and acquiring the coordinates of the m tracking mark points;
step S3, sequentially calculating the distance between each tracking mark point and the rest tracking mark points, wherein m tracking mark points obtain m groups of distances, and each group of distances has m-1 numerical values;
and S4, traversing m groups of distances of the m tracking mark points, sequentially matching m-1 numerical values with the k-1 numerical values obtained in the step S1, and realizing virtual mark point filtering according to a matching result.
Preferably, in step S1, a coordinate system is defined, coordinates of k real markers on the tracking object based on the coordinate system are obtained, one real marker is arbitrarily selected, and distances between the selected real marker and other markers are calculated to obtain k-1 values.
Preferably, in step S2, the coordinates of the m tracking mark points are the coordinates in the coordinate system.
Preferably, in step S2, the marker point tracking means acquires tracking marker point data using a binocular vision camera.
Preferably, in step S4, each set is sequentially processedDistance miAnd traversing m-1 values, and if k-1 values exist in the m-1 values and the corresponding relation is found in the k-1 values obtained in the step S1, the values are indicated to be valid, and the group of distances is obtained as valid distances.
Preferably, when k-1 values existing in the m-1 values can find corresponding values from the k-1 values obtained in step S1, and the absolute value error of the two values is less than or equal to a preset value, it indicates that the values are valid.
Preferably, from the m finally obtainediAnd in the group distance, the distance between a certain tracking mark point and other mark points is obtained, and finally the distances are mapped into coordinate values of the tracking mark points one by one to realize the filtering of the virtual mark points.
Preferably, the distance between the real mark points and the distance between the tracking mark points are calculated in a mean square error mode.
In order to achieve the above object, the present invention further provides a virtual mark point filtering system, including:
the real mark point distance calculation unit is used for acquiring coordinates of k real mark points on the tracked object, randomly selecting one real mark point, calculating the distance between the real mark point and other mark points, and acquiring k-1 numerical values;
a tracking mark point acquisition unit for tracking the mark points on the tracked object by using the mark point tracking device, acquiring the data of m tracking mark points acquired by the mark point tracking device and acquiring the coordinates of the m tracking mark points;
the tracking mark point distance calculating unit is used for calculating the distance between each tracking mark point and the rest tracking mark points in sequence, m groups of distances are obtained by the m tracking mark points, and each group of distances has m-1 numerical values;
and the distance matching unit is used for traversing m groups of distances of the m tracking mark points, sequentially matching the m-1 number values with the k-1 number values obtained by the real mark point distance calculation unit, and filtering the virtual mark points according to the matching result.
Preferably, the distance matching unit sequentially matches each group of distances miGo through m-1 values thereof as long as m-1 isIf there are k-1 values in the values and the corresponding relationship is found in the k-1 values obtained in step S1, it is indicated that the value is valid, and the set of distances is obtained as valid distances.
Compared with the prior art, the virtual mark point filtering method and the virtual mark point filtering system provided by the invention have the advantages that the distance between the real mark points is calculated firstly, the distance between the tracking mark points obtained by calculation is matched with the distance between the real mark points, so that the virtual mark points in the tracking mark points are filtered, and the correct identification and position acquisition of the mark points are realized.
Drawings
FIG. 1 is a schematic diagram of a binocular vision camera of the prior art;
FIG. 2 is a schematic view of a coordinate system of a prior art binocular vision camera;
FIG. 3 is a schematic diagram of a binocular vision camera of the prior art for determining the position of a marker;
FIG. 4 is a schematic diagram of a binocular vision camera of the prior art with virtual marker points;
FIG. 5 is a flowchart illustrating steps of a method for filtering virtual mark points according to the present invention;
FIG. 6 is a schematic diagram of a tracking object and its markers in an embodiment of the present invention;
FIG. 7 is a schematic diagram of marker point data that should be correctly identified by a binocular vision camera in an embodiment of the present invention;
FIG. 8 is a schematic diagram of all tracking marker point data actually obtained by a binocular vision camera in an embodiment of the present invention
FIG. 9 is a diagram of a system architecture of a virtual marker filtering system according to the present invention.
Detailed Description
Other advantages and capabilities of the present invention will be readily apparent to those skilled in the art from the present disclosure by describing the embodiments of the present invention with specific embodiments thereof in conjunction with the accompanying drawings. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention.
FIG. 5 is a flowchart illustrating steps of a method for filtering virtual mark points according to the present invention. As shown in fig. 5, the method for filtering virtual mark points of the present invention includes the following steps:
step S1, defining a coordinate system, obtaining the coordinates of k real mark points on the tracking object based on the coordinate system, arbitrarily selecting one real mark point, calculating the distance between the real mark point and other mark points, and obtaining k-1 numerical values. That is, according to the coordinates of any real mark point, the distance between the real mark point and other mark point coordinates is calculated, and k-1 numerical values are obtained.
In the embodiment of the present invention, the tracking object is set in the measuring range of the marker tracking device, the real marker is marked on the tracking object, the tracking object can be any object, such as a human body, in the embodiment of the present invention, the regular tracking object in the shape of a cube as shown in fig. 6 is taken as an example, and 5 markers are marked on the regular tracking object, and the markers are numbered Ball in sequence0～Ball4Assuming that a coordinate system is defined, with the X-axis down, the Y-axis left, and the Z-axis forward (relative to the device), the coordinates of each real marker point referenced to the coordinate system are measured by the scale definition on the tracker and with the help of a micrometer, and the results are as follows:
Ball0:(Tx0,Ty0,Tz0)
Ball1:(Tx1,Ty1,Tz1)
Ball2:(Tx2,Ty2,Tz2)
Ball3:(Tx3,Ty3,Tz3)
Ball4:(Tx4,Ty4,Tz4)
in a specific embodiment of the present invention, the distance between two points in space is calculated using a mean square error formula, which can be described as:
Figure RE-GDA0001949655500000051
for example, assume that the true marker point is Ball0Sequentially calculating the marking point Ball1For Ball2～Ball4The distance of (2) is obtained to be 4 distances, i.e. corresponding to 4 values.
Step S2, tracking the marker on the tracked object by the marker tracking device, acquiring the data of m tracking markers acquired by the marker tracking device, and acquiring the coordinates of m tracking markers in the coordinate system.
In the embodiment of the present invention, the marker tracking device uses a binocular vision camera, and takes the tracked object shown in fig. 6 as an example, and obtains the coordinates of m tracking markers by using the coordinate system defined in step S1. Ideally, the real-time positions of exactly 5 markers should be seen in the measurement range (as shown in fig. 7). However, in general, it is difficult to put the position of the tracking tool well, so that a plurality of mark points are parallel to the device, or the mark points recognized by the device are coplanar, and at this time, the situation shown in fig. 8 occurs, and it can be seen that the number of obtained mark points should be 5, and the number of obtained tracking mark points is 7, that is, two invalid virtual mark points exist in the obtained mark point data, and in order to obtain a correct mark result, the two virtual mark points need to be filtered.
And step S3, sequentially calculating the distance between each tracking mark point and the rest tracking mark points, wherein m groups of distances can be obtained by m tracking mark points, and each group of distances has m-1 numerical values. That is, traversing all tracking mark points to find the distance between the current tracking mark point and the remaining other tracking mark points, in the embodiment of the present invention, similarly using the mean square error formula, for m tracking mark points, m groups of distances are calculated, each group of distances includes m-1 values, and the m groups of distances are stored in the variables of the type List < float [ m-1 ].
Step S4, traversing m groups of distances of m tracking mark points, and sequentially connecting m-1 numerical values with k-1 numerical values (m-1) obtained in step S1>K-1), and filtering the virtual mark points according to the matching result. In particular, the amount of the solvent to be used,after m groups of distances of m tracking mark points are obtained through calculation, sequentially comparing the distance m of each groupiTraversing m-1 numerical values thereof as long as k-1 numerical values exist in the m-1 numerical values, and finding a corresponding relation in the k-1 numerical values obtained in the step S1, namely, the absolute value error of the two numerical values is less than or equal to the preset value { | (m-1)i–(k-1)iAnd | ≦ 1}, which indicates that the value is valid, i.e., that the group distance is a valid distance. Here, if m-1 is k-1, it indicates that there is no virtual marker point, and it is not necessary to perform distance matching.
In an embodiment of the present invention, it is assumed that the true marker point selection k0As reference coordinates, k is calculated0And k isn-1Generating k-1 numerical values by the distance of each coordinate, circularly traversing m tracking mark points, and calculating miAnd mn-1Generating m groups of distances by the distance between the coordinates, wherein each group of distances has m-1 numerical values, traversing the m groups of distances, matching the m-1 numerical values with the k-1 numerical values, and if the k-1 numerical values in the m-1 numerical values are matched with the k-1 numerical values corresponding to the real mark points, matching the m-1 numerical values to obtain m matched numerical valuesiThe group distance is the effective distance, and m is obtained from the final productiIn the group distance, the distance between a certain tracking mark point and other mark points can be known, and finally the distances are mapped into coordinate values of the tracking mark points one by one, so that the filtering of the virtual mark points can be completed.
FIG. 9 is a diagram of a system architecture of a virtual marker filtering system according to the present invention. As shown in fig. 9, the virtual mark point filtering system of the present invention includes the following steps:
the real mark point distance calculation unit 101 is configured to define a coordinate system, obtain coordinates of k real mark points on the tracking object based on the coordinate system, arbitrarily select one real mark point, calculate a distance between the selected real mark point and another mark point, and obtain k-1 numerical values. That is, according to the coordinates of any real mark point, the distance between the real mark point and the coordinates of other mark points is calculated, and k-1 numerical values are obtained.
In the embodiment of the invention, the tracking object is arranged in the measuring range of the marking point tracking device, the real marking point is marked on the tracking object,the tracking object may be any object, such as a human body, and in one embodiment of the invention, 5 markers are marked on the tracking object, and the markers are sequentially numbered Ball0～Ball4Assuming that a coordinate system is defined, the X-axis is downward, the Y-axis is leftward, and the Z-axis is forward (relative to the device), the coordinates of each real mark point based on the coordinate system are measured by the scale definition on the tool and by the micrometer, and the results are as follows:
Ball0:(Tx0,Ty0,Tz0)
Ball1:(Tx1,Ty1,Tz1)
Ball2:(Tx2,Ty2,Tz2)
Ball3:(Tx3,Ty3,Tz3)
Ball4:(Tx4,Ty4,Tz4)
in a specific embodiment of the present invention, the distance between two points in space is calculated using a mean square error formula, which can be described as:
Figure RE-GDA0001949655500000071
for example, assume that the true marker point is Ball0Sequentially calculating the marking point Ball1For Ball2～Ball4The distance of (2) is obtained to be 4 distances, i.e. corresponding to 4 values.
A tracking mark point obtaining unit 102, configured to track a mark point on the tracked object by using the mark point tracking device, obtain data of m tracking mark points obtained by the mark point tracking device, and obtain coordinates of the m tracking mark points in the coordinate system. In the embodiment of the present invention, the marker tracking device employs a binocular vision camera, and the coordinate system used is still the coordinate system defined by the real marker distance calculating unit 101.
And the tracking mark point distance calculating unit 103 is used for calculating the distance between each tracking mark point and the rest tracking mark points in sequence, wherein m groups of distances can be obtained by the m tracking mark points, and each group of distances has m-1 numerical values. That is, the tracking mark point distance calculating unit 103 traverses all tracking mark points to find the distance between the current tracking mark point and the remaining other tracking mark points, and in the embodiment of the present invention, it also uses the mean square error formula to calculate m groups of distances for m tracking mark points, where each group of distances includes m-1 values, and stores the m groups of distances into the List < float [ m-1] > type variables.
A distance matching unit 104 for traversing m groups of distances of the m tracking mark points, and sequentially matching m-1 values with k-1 values (m-1) obtained in step S1>K-1), and filtering the virtual mark points according to the matching result. Specifically, after m groups of distances of m tracking mark points are calculated, the distance matching unit 104 sequentially compares the distances m of each groupiTraversing m-1 numerical values thereof as long as k-1 numerical values exist in the m-1 numerical values, and finding a corresponding relation in the k-1 numerical values obtained in the step S1, namely, the absolute value error of the two numerical values is less than or equal to the preset value { | (m-1)i–(k-1)iAnd | ≦ 1}, which indicates that the value is valid, i.e., that the group of distances is valid. Here, if m-1 is k-1, it indicates that there is no virtual marker point, and it is not necessary to perform distance matching.
In an embodiment of the present invention, it is assumed that the true marker point selection k0As reference coordinates, k is calculated0And k isn-1Generating k-1 numerical values by the distance of each coordinate, circularly traversing m tracking mark points, and calculating miAnd mn-1Generating m groups of distances by the distance between the coordinates, wherein each group of distances has m-1 numerical values, traversing the m groups of distances, matching the m-1 numerical values with the k-1 numerical values, and if the k-1 numerical values in the m-1 numerical values are matched with the k-1 numerical values corresponding to the real mark points, matching the m-1 numerical values to obtain m matched numerical valuesiThe group distance is the effective distance, and m is obtained from the final productiIn the group distance, the distance between a certain tracking mark point and other mark points can be known, and finally the distances are mapped into coordinate values of the tracking mark points one by one, so that the filtering of the virtual mark points can be completed.
In summary, the virtual mark point filtering method and system of the present invention first calculate the distance between the real mark points, and match the calculated distance between the tracking mark points with the distance between the real mark points, so as to filter the virtual mark points in the tracking mark points, thereby realizing correct identification and position acquisition of the mark points.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Modifications and variations can be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the present invention. Therefore, the scope of the invention should be determined from the following claims.

Claims (9)

1. A virtual mark point filtering method comprises the following steps:
step S1, acquiring the coordinates of k real mark points on the tracked object, randomly selecting one real mark point, calculating the distance between the real mark point and other mark points, and acquiring k-1 numerical values;
step S2, tracking the mark points on the tracked object by using the mark point tracking device, acquiring the data of m tracking mark points acquired by the mark point tracking device, and acquiring the coordinates of the m tracking mark points;
step S3, sequentially calculating the distance between each tracking mark point and the rest tracking mark points, wherein m tracking mark points obtain m groups of distances, and each group of distances has m-1 numerical values;
step S4, traversing m groups of distances of m tracking mark points, matching m-1 numerical values with the k-1 numerical values obtained in the step S1 in sequence, and realizing virtual mark point filtering according to matching results, wherein the steps are as follows: after m groups of distances of m tracking mark points are obtained through calculation, sequentially comparing the distance m of each groupiAnd traversing m-1 numerical values, if k-1 numerical values exist in the m-1 numerical values and the corresponding relation is found in the k-1 numerical values obtained in the step S1, the numerical values are valid, and the group of distances are obtained as valid distances.
2. The method for filtering virtual mark points as claimed in claim 1, wherein: in step S1, a coordinate system is defined, coordinates of k real markers on the tracking object based on the coordinate system are obtained, one real marker is arbitrarily selected, and distances between the selected real marker and other markers are calculated to obtain k-1 values.
3. The method for filtering virtual mark points as claimed in claim 2, wherein: in step S2, the coordinates of the m tracking mark points are the coordinates in the coordinate system.
4. The method for filtering virtual mark points as claimed in claim 1, wherein: in step S2, the marker tracking apparatus acquires tracking marker point data using a binocular vision camera.
5. The method for filtering virtual mark points as claimed in claim 1, wherein: when k-1 values existing in the m-1 values can find corresponding values in the k-1 values obtained in the step S1, and the absolute value error of the two values is less than or equal to a preset value, the value is valid.
6. The method for filtering virtual mark points as claimed in claim 1, wherein: from the m finally obtainediAnd in the group distance, the distance between a certain tracking mark point and other mark points is obtained, and finally the distances are mapped into coordinate values of the tracking mark points one by one to realize the filtering of the virtual mark points.
7. The method for filtering virtual mark points as claimed in claim 1, wherein: the distance calculation between the real mark points and the distance calculation between the tracking mark points adopt a mean square error mode.
8. A virtual marker filtering system, comprising:
the real mark point distance calculation unit is used for acquiring coordinates of k real mark points on the tracked object, randomly selecting one real mark point, calculating the distance between the real mark point and other mark points, and acquiring k-1 numerical values;
a tracking mark point acquisition unit for tracking the mark points on the tracked object by using the mark point tracking device, acquiring the data of m tracking mark points acquired by the mark point tracking device and acquiring the coordinates of the m tracking mark points;
the distance calculation unit of the tracking mark points is used for calculating the distance between each tracking mark point and the rest tracking mark points in sequence, m groups of distances are obtained by m tracking mark points, and each group of distances has m-1 numerical values;
the distance matching unit is used for traversing m groups of distances of m tracking mark points, matching m-1 numerical values with the k-1 numerical values obtained by the real mark point distance calculation unit in sequence, and realizing virtual mark point filtering according to matching results, and specifically comprises the following steps: after m groups of distances of m tracking mark points are obtained through calculation, sequentially comparing the distance m of each groupiTraversing m-1 numerical values, if k-1 numerical values exist in the m-1 numerical values and the corresponding relation is found in the k-1 numerical values obtained by the real mark point distance calculation unit, indicating that the numerical values are effective, and obtaining the group of distances as effective distances.
9. The virtual marker point filtering system of claim 8, wherein: the distance matching unit sequentially compares the distance m of each groupiAnd traversing m-1 numerical values, and if k-1 numerical values exist in the m-1 numerical values and the corresponding relation is found in the k-1 numerical values obtained in the step S1, indicating that the numerical values are effective and obtaining the group of distances as effective distances.
CN201811360233.7A 2018-11-15 2018-11-15 Virtual mark point filtering method and system Active CN109410277B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201811360233.7A CN109410277B (en) 2018-11-15 2018-11-15 Virtual mark point filtering method and system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201811360233.7A CN109410277B (en) 2018-11-15 2018-11-15 Virtual mark point filtering method and system

Publications (2)

Publication Number Publication Date
CN109410277A CN109410277A (en) 2019-03-01
CN109410277B true CN109410277B (en) 2022-03-08

Family

ID=65473351

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201811360233.7A Active CN109410277B (en) 2018-11-15 2018-11-15 Virtual mark point filtering method and system

Country Status (1)

Country Link
CN (1) CN109410277B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111426268B (en) * 2020-04-20 2021-09-24 武汉大学中南医院 Binocular vision camera matching method

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN204539353U (en) * 2014-12-29 2015-08-05 深圳超多维光电子有限公司 Medical image three-dimensional display system
CN105812774A (en) * 2014-12-29 2016-07-27 广东省明医医疗慈善基金会 Three-dimensional display system based on endoscope and method thereof
CN107595388A (en) * 2017-08-01 2018-01-19 华南理工大学 A kind of near infrared binocular visual stereoscopic matching process based on witch ball mark point

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN204539353U (en) * 2014-12-29 2015-08-05 深圳超多维光电子有限公司 Medical image three-dimensional display system
CN105812774A (en) * 2014-12-29 2016-07-27 广东省明医医疗慈善基金会 Three-dimensional display system based on endoscope and method thereof
CN107595388A (en) * 2017-08-01 2018-01-19 华南理工大学 A kind of near infrared binocular visual stereoscopic matching process based on witch ball mark point

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
Design and Evaluation of a System for Microscope-Assisted Guided Interventions (MAGI);Philip J. Edwards;《Springer-Verlag Berlin Heidelberg》;19991231;842-852 *

Also Published As

Publication number Publication date
CN109410277A (en) 2019-03-01

Similar Documents

Publication Publication Date Title
CA3013128C (en) Methods and systems for updating an existing landmark registration
KR101723765B1 (en) Pose determination from a pattern of four leds
US9622824B2 (en) Method for automatically identifying instruments during medical navigation
US20060173357A1 (en) Patient registration with video image assistance
US11896441B2 (en) Systems and methods for measuring a distance using a stereoscopic endoscope
US10624540B2 (en) Method and instrument for surgical navigation
Deacon et al. The Pathfinder image-guided surgical robot
CN107595388B (en) Near-infrared binocular vision stereo matching method based on reflective ball mark points
CN114469343A (en) Calibration piece, surgical navigation coordinate system registration system, method, device and medium
WO2020264489A1 (en) Tracker-based surgical navigation
CN109410277B (en) Virtual mark point filtering method and system
Haase et al. ToF/RGB sensor fusion for 3-D endoscopy
Yamauchi et al. Calibration of a structured light system by observing planar object from unknown viewpoints
CN109091228B (en) Multi-instrument optical positioning method and system
JP4750197B2 (en) Endoscope device
CN113066126A (en) Positioning method for puncture needle point
CN111110348B (en) Positioning method, positioning device, positioning system and computer readable storage medium
Steinicke et al. Generating optimized marker-based rigid bodies for optical tracking systems.
CN115517783A (en) High-precision surgical tool positioning method and system based on TOF sensor
RU2065133C1 (en) Method of automated measurement of coordinates of points of external medium to plot its three-dimensional model in stereo television system of technical vision
US20240115325A1 (en) Camera tracking system for computer assisted surgery navigation
Jianxi et al. Calibrating method and systemic error analysis on binocular 3D position system
TW201818347A (en) The method of complete endoscopic MIS instrument 3D position estimation using a single 2D image
Chiu et al. 3D Position Estimation of Endoscopic Surgical Instruments: A Comparison of Monocular and Binocular Algorithms Using on IR Markers
CN115068109A (en) Infrared target identification method and device for medical operation navigation

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant