CN112085762A - Target position prediction method based on curvature radius and storage medium - Google Patents
Target position prediction method based on curvature radius and storage medium Download PDFInfo
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Abstract
The invention discloses a target position prediction method based on curvature radius and a storage medium, wherein the method comprises the following steps: establishing a three-dimensional rectangular coordinate system; respectively calculating coordinates of the position center point of the target in the three RGB-D images; obtaining a first plane according to the three position central points and calculating an equation of the first plane; projecting the three position center points to an XOY plane; fitting the three projection points by using a circular equation or a parabolic equation, and calculating the curvature radius of the motion curve at the last projection point; calculating the instantaneous speed according to the curvature radius; calculating the displacement of the target in the X-axis direction according to the frame interval time and the instantaneous speed; calculating a plane prediction point of the target on the motion curve according to the coordinate and the displacement of the last projection point; and drawing a perpendicular line of the XOY plane through the plane prediction point, and calculating the coordinates of the intersection point of the perpendicular line and the first plane to obtain a predicted position point of the target. The invention can predict the position of the object in the three-dimensional space.
Description
Technical Field
The present invention relates to the field of target position prediction technologies, and in particular, to a target position prediction method based on a curvature radius and a storage medium.
Background
The target tracking and predicting algorithm is applied to a plurality of intelligent monitoring devices, such as intelligent security cameras, unmanned planes, robots and the like. The traditional camera mainly acquires an RGB image of a target, and performs target recognition, tracking and position prediction on the RGB image. With the continuous development of camera technology, some depth cameras using structured light appear in the market, and besides a conventional RGB lens, the depth information of an object is obtained by using the structured light. The latest technology can utilize structured light to carry out three-dimensional modeling on an object and a space, and a plurality of point cloud pictures are spliced to form a complete three-dimensional point cloud space.
At present, an object tracking task and a position prediction task in a three-dimensional point cloud space have no targeted algorithm, although the traditional meanshift algorithm can be applied to object tracking in the three-dimensional space, the accuracy is not enough, particularly, when the tracking is shielded by other objects, the tracking is easy to be followed by mistake, and the position needs to be predicted to carry out position verification.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: a target position prediction method and a storage medium based on curvature radius are provided, which can predict the position of a target object in the next frame in a three-dimensional space and have high prediction accuracy.
In order to solve the technical problems, the invention adopts the technical scheme that: a curvature radius-based target location prediction method, comprising:
acquiring an RGB image, and establishing a three-dimensional rectangular coordinate system according to the RGB image;
respectively calculating coordinates of the position center point of the target in the three RGB-D images;
determining a plane according to the three position central points to obtain a first plane, and calculating an equation of the first plane;
projecting the three position central points to an XOY plane to obtain three projection points, and calculating coordinates of the three projection points;
fitting the three projection points by using a circular equation or a parabolic equation to obtain a motion curve, and calculating the curvature radius of the motion curve at the last projection point;
calculating the instantaneous speed of the target at the last projection point according to the curvature radius;
calculating the displacement of the target in the X-axis direction according to the frame interval time and the instantaneous speed;
calculating a plane prediction point of a target on the motion curve according to the coordinate of the last projection point and the displacement in the X-axis direction;
and drawing a perpendicular line of the XOY plane through the plane prediction point, and calculating the coordinates of the intersection point of the perpendicular line and the first plane to obtain a predicted position point of the target.
The invention also relates to a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps as described above.
The invention has the beneficial effects that: fitting a curve in a three-dimensional space according to the position center point of the target object in the three-frame depth image, calculating the curvature radius of the position of the point on the curve, then calculating the instantaneous speed of the target in the third-frame depth image, and finally predicting the position of the target object in the next-frame depth image by using the obtained instantaneous speed; the space curve is projected onto the plane by adopting a projection method, so that the calculation difficulty can be reduced, and the calculation efficiency can be improved; by utilizing the curve to fit the motion track and then utilizing the curvature radius to calculate the instantaneous speed, the calculated result error can be ensured to be smaller, thereby ensuring the accuracy of subsequent position prediction. The method can predict the position of the object in the three-dimensional space, has high accuracy, does not need to model the motion trail of the target object in one step in advance, and can be used as an auxiliary means for the object tracking task in the three-dimensional space to carry out position verification.
Drawings
FIG. 1 is a flow chart of a method for predicting a target location based on a radius of curvature according to the present invention;
fig. 2 is a flowchart of a method according to a first embodiment of the invention.
Detailed Description
In order to explain technical contents, objects and effects of the present invention in detail, the following detailed description is given with reference to the accompanying drawings in conjunction with the embodiments.
The most key concept of the invention is as follows: and fitting the motion track by using a curve, calculating the instantaneous speed by using the curvature radius, calculating the displacement by using the instantaneous speed and the frame interval time, and predicting the position of the next frame by using the displacement.
Referring to fig. 1, a method for predicting a target position based on a curvature radius includes:
acquiring an RGB image, and establishing a three-dimensional rectangular coordinate system according to the RGB image;
respectively calculating coordinates of the position center point of the target in the three RGB-D images;
determining a plane according to the three position central points to obtain a first plane, and calculating an equation of the first plane;
projecting the three position central points to an XOY plane to obtain three projection points, and calculating coordinates of the three projection points;
fitting the three projection points by using a circular equation or a parabolic equation to obtain a motion curve, and calculating the curvature radius of the motion curve at the last projection point;
calculating the instantaneous speed of the target at the last projection point according to the curvature radius;
calculating the displacement of the target in the X-axis direction according to the frame interval time and the instantaneous speed;
calculating a plane prediction point of a target on the motion curve according to the coordinate of the last projection point and the displacement in the X-axis direction;
and drawing a perpendicular line of the XOY plane through the plane prediction point, and calculating the coordinates of the intersection point of the perpendicular line and the first plane to obtain a predicted position point of the target.
From the above description, the beneficial effects of the present invention are: the method can predict the position of the object in the three-dimensional space, and has high accuracy.
Further, the establishing of the three-dimensional rectangular coordinate system according to the RGB image specifically includes:
use the upper left corner of RGB image is the original point to use the ray of crossing original point and vertical decurrent to be Y axle positive direction, use the ray of crossing original point and level right to be Z axle positive direction, use and cross original point and perpendicular to the ray of the inside direction of RGB image is Z axle positive direction, establishes three-dimensional rectangular coordinate system.
Further, after the projecting the three position central points to the XOY plane to obtain three projection points and calculating coordinates of the three projection points, the method further includes:
judging whether the three projection points are on the same straight line or not;
if yes, transforming the projection plane;
if not, the step of fitting the three projection points by using a circular equation or a parabolic equation to obtain a motion curve and calculating the curvature radius of the motion curve at the last projection point is executed.
As can be seen from the above description, when three projection points are collinear, the projection points are made non-collinear by transforming the plane of projection.
Further, fitting the three projection points by using a circular equation or a parabolic equation to obtain a motion curve, and calculating a curvature radius of the motion curve at the last projection point specifically as follows:
judging whether the X coordinates of two projection points in the three projection points have equal values or not;
if the three projection points exist, fitting the three projection points through a circular equation to obtain a motion curve, and calculating the curvature radius of the motion curve at the last projection point;
if not, fitting the three projection points by using a parabolic equation to obtain a motion curve, and calculating the curvature radius of the motion curve at the last projection point.
As can be seen from the above description, when the X coordinate values of the two projection points are equal, the equation of the parabola is not solved, and therefore, a circular equation is used for fitting.
Further, the calculating the instantaneous speed of the target at the last projection point according to the curvature radius specifically includes:
calculating an included angle between the normal direction of the motion curve at the last projection point and the gravity direction;
calculating the instantaneous speed of the target at the last projection point according to a first formula, wherein the first formula is mv2Where m is the target mass, v is the instantaneous velocity, r is the radius of curvature, g is the acceleration of gravity, and θ is the angle.
From the above description, the instantaneous velocity is calculated by using the formula of the centripetal force of the curvilinear motion and the principle that the formula of the centripetal force is the component of the gravity of the object in the normal direction of the curve.
Further, the calculating the displacement of the target in the X-axis direction according to the frame interval time and the instantaneous speed specifically includes:
calculating an X-axis component of the instantaneous velocity by orthogonal decomposition;
and calculating the displacement of the target in the X-axis direction according to the frame interval time and the X-axis component.
As can be seen from the above description, the displacement amount of the object between the adjacent two frame images is calculated using the instantaneous speed and the frame interval time.
Further, the step of making a perpendicular line of the XOY plane through the plane prediction point, and calculating coordinates of an intersection point of the perpendicular line and the first plane to obtain a predicted position point of the target specifically includes:
drawing a perpendicular line of an XOY plane through the plane prediction point, and calculating an equation of the perpendicular line;
and calculating the coordinates of the intersection point of the perpendicular line and the first plane according to the equation of the perpendicular line and the equation of the first plane to obtain the predicted position point of the target.
From the above description, theoretically, the curve in the XOY plane is translated in the positive direction of the Z axis to form a curved plane, and the curve of the curved plane intersecting the first plane Q is the motion curve of the object in the three-dimensional space.
The invention also proposes a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps as described above.
Example one
Referring to fig. 2, a first embodiment of the present invention is: a target position prediction method based on curvature radius can predict the position of a target object in a three-dimensional point cloud space, is suitable for intelligent monitoring equipment such as a depth camera, mainly tracks and predicts falling objects in life, such as the tracks of objects such as basketball, volleyball, table tennis and the like (hit rate prediction can be carried out subsequently), and comprises the following steps:
s1: acquiring an RGB image, and establishing a three-dimensional rectangular coordinate system according to the RGB image; specifically, in this embodiment, a three-dimensional rectangular coordinate system is established with the upper left corner of the RGB image as an origin, the ray passing through the origin and vertically downward as the positive Y-axis direction, the ray passing through the origin and horizontally rightward as the positive X-axis direction, and the ray passing through the origin and perpendicular to the inward direction of the RGB image as the positive Z-axis direction.
S2: respectively calculating coordinates of the position center point of the target in the three RGB-D images; that is, the position center points of one target are obtained in three frames of RGB-D images (depth images), that is, three position center points are obtained in total, and P is assumed to be sequentially arranged1、P2、P3。
Wherein, the three frames of RGB-D images can be three continuous frames or discontinuous; the purpose of the method is to predict the position point P of the target in the RGB-D image of the frame next to the last frame of the three RGB-D images4. The time interval between each frame needs to be known.
Further, in this embodiment, all point coordinates of the target may be obtained from the three-dimensional point cloud corresponding to the three frames of RGB-D images, and then an average value of all point coordinates is calculated as the coordinates of the position center point of the target.
S3: and judging whether the three position central points are on the same straight line, if so, exiting, namely not predicting the straight line motion, and if not, executing the step S4, wherein the method only predicts the positions of the curvilinear motion.
S4: according to three positionsAnd centering the point, determining a plane, obtaining a first plane, and calculating an equation of the first plane. According to the principle that three points determine one plane, the first plane Q can be obtained according to three non-collinear position center points, and the equation is a1X+b1Y+c1Z+d10, wherein the three position center points P are substituted1、P2And P3To obtain a1、b1、c1And d1。
S5: and projecting the three position central points to an XOY plane to obtain three projection points, and calculating coordinates of the three projection points. Assuming three position center points P1、P2、P3The corresponding projection points are respectively P1’、P2’、P3', then order P1、P2、P3The value of Z axis in the coordinate values of (A) is zero, and then P can be obtained1’、P2’、P3' coordinates of.
S6: and judging whether the three projection points are on the same straight line, if so, executing the step S7, and if not, executing the step S8.
S7: and transforming a projection plane, such as projecting the three position center points to a ZOY plane. Since the above steps have ensured three position center points P1、P2、P3Not collinear in space, so that when three projection points are collinear, they can be made non-collinear by transforming the projection plane. Further, for the purpose of format unification, the present embodiment implements transformation of the projection plane by exchanging the X-axis and the Z-axis of the three-dimensional rectangular coordinate system, and recalculates the three location center points P1、P2、P3And the equation of the first plane Q, i.e., return to the execution of step S2.
Furthermore, the new coordinates of the center points of the three positions can be quickly obtained by exchanging the X value and the Z value in the coordinates of the center points of the original positions, and the coefficients of the X and the Z in the equation of the original first plane are exchanged, namely, the a is exchanged1And c1And a new equation of the first plane can be obtained quickly.
In the present embodiment, it is considered that the parabola of the object moving in the air is mostly open downward, i.e., the opening is along the Y-axis direction, and therefore, the projection to the XOY plane or the ZOY plane is convenient for calculation.
S8: and judging whether the X coordinate values of two projection points in the three projection points are equal, if so, executing step S9, and if not, executing step S10.
S9: and fitting the three projection points through a circular equation to obtain a motion curve, and calculating the curvature radius of the motion curve at the last projection point. Specifically, three projection points P1’、P2’、P3' coordinate substitution into circular equation (X-a)2)2+(Y-b2)2＝R2Obtaining a2、b2And R, the radius of curvature of the circle is the radius of the circle, so the radius of curvature R of the motion curve at the last projection point is R. Step S11 is executed.
S10: and fitting the three projection points by using a parabolic equation to obtain a motion curve, and calculating the curvature radius of the motion curve at the last projection point. Specifically, three projection points P1’、P2’、P3' coordinate substitution into parabolic equation Y ═ a3X2+b3X+c3Obtaining a3、b3And c3(ii) a Then, an equation of the curvature radius r with respect to X is deduced according to the curvature formula, and r is obtained as [1+ (2 a)3X+b3)2]3/2/|2a3L, |; will P3The X coordinate value of' is substituted into the curvature radius equation to obtain the curvature radius of the motion curve at the last projection point. Step S11 is executed.
Further, not shown in the figure, if the system of three projection points substituted into the parabolic equation has no solution, step S9 is executed.
S11: and calculating the instantaneous speed of the target at the last projection point according to the curvature radius. Specifically, the centripetal force formula of curvilinear motion in physics is utilized: f ═ mv2Method for solving object motion to point P by/r3Instantaneous speed at, because of centripetal force F is the object curvingThe component of the line normal upward (in this embodiment, the air resistance to the motion of the object is ignored, and the motion of the object in the air is assumed to be only acted on by gravity), so F is mgcos θ, and mv can be obtained2Mgcos θ; the mass m can be reduced and then derived as v2Where v is the instantaneous velocity, r is the radius of curvature calculated in step S9 or S10, g is the acceleration due to gravity, and θ is the motion curve at point P3The angle between the normal and the gravity direction at' is perpendicular to the tangent of the curve, and can be calculated by the existing calculation method.
S12: calculating the displacement of the target in the X-axis direction according to the frame interval time and the instantaneous speed; the frame interval time, i.e., the time interval between two adjacent frames, is numerically equal to the reciprocal of the frame rate, in seconds. Specifically, the X-axis component v of the instantaneous velocity is first calculated by orthogonal decompositionx(ii) a Then, according to the frame interval time and the X-axis component of the instantaneous speed, calculating the displacement of the next frame of the target in the X-axis direction, i.e. letting v bexMultiplying the frame interval time to calculate the displacement delta of the next frame in the X-axis directionx。
S13: calculating a plane prediction point P of the target on the motion curve according to the coordinate of the last projection point and the displacement in the X-axis direction4' i.e. calculating the position of the object on the motion curve, P, of the next frame4' X-axis coordinate value, i.e. point P3' the X-axis coordinate value plus the X-axis displacement is denoted as X3+ΔxX is to be3+ΔxSubstituting the X into the parabolic equation in step S10, and using the obtained Y as P4' Y-axis coordinate value, i.e. P4' coordinates in the XOY plane are (x)3+Δx，YParabola line(x3+Δx))。
S14: and drawing a perpendicular line of the XOY plane through the plane prediction point, and calculating the coordinates of the intersection point of the perpendicular line and the first plane to obtain a predicted position point of the target. Specifically, a perpendicular to the XOY plane is made through the plane prediction point, and the perpendicular intersects the first plane Q at a point P4By simultaneous firstThe equation of the plane Q and the equation of the perpendicular line can be used to calculate the point P4The coordinates of (a). Point P4I.e. the predicted position of the object in the next frame of RGB-D image.
Theoretically, the curve in the XOY plane is translated in the positive direction of the Z axis to form a curve plane, and the curve of the intersection of the curve plane and the first plane Q is the motion curve of the target in the three-dimensional space. Since the curve equation in the three-dimensional space is directly calculated to be too complex, the curve equation is projected to the XOY plane first, and the motion curve on the XOY plane is solved, so that the calculation process can be simplified.
The method can predict the position of the object in the three-dimensional space, has high accuracy, does not need to model the motion trail of the target object in advance at one time, and models the object in real time through the position of any three frames; the motion track is fitted by using a curve, and the instantaneous speed is calculated by using the curvature radius, so that the error is small; meanwhile, the method can be used as an auxiliary means for an object tracking task in a three-dimensional space to carry out position verification.
Example two
The present embodiment is a computer-readable storage medium corresponding to the above-mentioned embodiments, on which a computer program is stored, which when executed by a processor implements the steps of:
acquiring an RGB image, and establishing a three-dimensional rectangular coordinate system according to the RGB image;
respectively calculating coordinates of the position center point of the target in the three RGB-D images;
determining a plane according to the three position central points to obtain a first plane, and calculating an equation of the first plane;
projecting the three position central points to an XOY plane to obtain three projection points, and calculating coordinates of the three projection points;
fitting the three projection points by using a circular equation or a parabolic equation to obtain a motion curve, and calculating the curvature radius of the motion curve at the last projection point;
calculating the instantaneous speed of the target at the last projection point according to the curvature radius;
calculating the displacement of the target in the X-axis direction according to the frame interval time and the instantaneous speed;
calculating a plane prediction point of a target on the motion curve according to the coordinate of the last projection point and the displacement in the X-axis direction;
and drawing a perpendicular line of the XOY plane through the plane prediction point, and calculating the coordinates of the intersection point of the perpendicular line and the first plane to obtain a predicted position point of the target.
Further, the establishing of the three-dimensional rectangular coordinate system according to the RGB image specifically includes:
use the upper left corner of RGB image is the original point to use the ray of crossing original point and vertical decurrent to be Y axle positive direction, use the ray of crossing original point and level right to be X axle positive direction, use and cross original point and perpendicular to the ray of the inside direction of RGB image is Z axle positive direction, establishes three-dimensional rectangular coordinate system.
Further, after the projecting the three position central points to the XOY plane to obtain three projection points and calculating coordinates of the three projection points, the method further includes:
judging whether the three projection points are on the same straight line or not;
if yes, transforming the projection plane;
if not, the step of fitting the three projection points by using a circular equation or a parabolic equation to obtain a motion curve and calculating the curvature radius of the motion curve at the last projection point is executed.
Further, fitting the three projection points by using a circular equation or a parabolic equation to obtain a motion curve, and calculating a curvature radius of the motion curve at the last projection point specifically as follows:
judging whether the X coordinates of two projection points in the three projection points have equal values or not;
if the three projection points exist, fitting the three projection points through a circular equation to obtain a motion curve, and calculating the curvature radius of the motion curve at the last projection point;
if not, fitting the three projection points by using a parabolic equation to obtain a motion curve, and calculating the curvature radius of the motion curve at the last projection point.
Further, the calculating the instantaneous speed of the target at the last projection point according to the curvature radius specifically includes:
calculating an included angle between the normal direction of the motion curve at the last projection point and the gravity direction;
calculating the instantaneous speed of the target at the last projection point according to a first formula, wherein the first formula is mv2Where m is the target mass, v is the instantaneous velocity, r is the radius of curvature, g is the acceleration of gravity, and θ is the angle.
Further, the calculating the displacement of the target in the X-axis direction according to the frame interval time and the instantaneous speed specifically includes:
calculating an X-axis component of the instantaneous velocity by orthogonal decomposition;
and calculating the displacement of the target in the X-axis direction according to the frame interval time and the X-axis component.
Further, the step of making a perpendicular line of the XOY plane through the plane prediction point, and calculating coordinates of an intersection point of the perpendicular line and the first plane to obtain a predicted position point of the target specifically includes:
drawing a perpendicular line of an XOY plane through the plane prediction point, and calculating an equation of the perpendicular line;
and calculating the coordinates of the intersection point of the perpendicular line and the first plane according to the equation of the perpendicular line and the equation of the first plane to obtain the predicted position point of the target.
In summary, according to the target position prediction method based on the curvature radius and the storage medium provided by the present invention, a curve in a three-dimensional space is fitted according to the position center point of the target object in the three frames of depth images, the curvature radius of the position of the point on the curve is calculated, the instantaneous speed of the target in the third frame of depth image is calculated, and finally the position of the target object in the next frame of depth image is predicted by using the calculated instantaneous speed; the space curve is projected onto the plane by adopting a projection method, so that the calculation difficulty can be reduced, and the calculation efficiency can be improved; by utilizing the curve to fit the motion track and then utilizing the curvature radius to calculate the instantaneous speed, the calculated result error can be ensured to be smaller, thereby ensuring the accuracy of subsequent position prediction. The method can predict the position of the object in the three-dimensional space, has high accuracy, does not need to model the motion trail of the target object in one step in advance, and can be used as an auxiliary means for the object tracking task in the three-dimensional space to carry out position verification.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all equivalent changes made by using the contents of the present specification and the drawings, or applied directly or indirectly to the related technical fields, are included in the scope of the present invention.
Claims (8)
1. A target position prediction method based on a curvature radius is characterized by comprising the following steps:
acquiring an RGB image, and establishing a three-dimensional rectangular coordinate system according to the RGB image;
respectively calculating coordinates of the position center point of the target in the three RGB-D images;
determining a plane according to the three position central points to obtain a first plane, and calculating an equation of the first plane;
projecting the three position central points to an XOY plane to obtain three projection points, and calculating coordinates of the three projection points;
fitting the three projection points by using a circular equation or a parabolic equation to obtain a motion curve, and calculating the curvature radius of the motion curve at the last projection point;
calculating the instantaneous speed of the target at the last projection point according to the curvature radius;
calculating the displacement of the target in the X-axis direction according to the frame interval time and the instantaneous speed;
calculating a plane prediction point of a target on the motion curve according to the coordinate of the last projection point and the displacement in the X-axis direction;
and drawing a perpendicular line of the XOY plane through the plane prediction point, and calculating the coordinates of the intersection point of the perpendicular line and the first plane to obtain a predicted position point of the target.
2. The method for predicting a target position based on a curvature radius according to claim 1, wherein the establishing a three-dimensional rectangular coordinate system according to the RGB images specifically comprises:
use the upper left corner of RGB image is the original point to use the ray of crossing original point and vertical decurrent to be Y axle positive direction, use the ray of crossing original point and level right to be X axle positive direction, use and cross original point and perpendicular to the ray of the inside direction of RGB image is Z axle positive direction, establishes three-dimensional rectangular coordinate system.
3. The method of predicting a target position based on a curvature radius of claim 1, wherein after the projecting the three position center points to an XOY plane to obtain three projection points and calculating coordinates of the three projection points, the method further comprises:
judging whether the three projection points are on the same straight line or not;
if yes, transforming the projection plane;
if not, the step of fitting the three projection points by using a circular equation or a parabolic equation to obtain a motion curve and calculating the curvature radius of the motion curve at the last projection point is executed.
4. The method for predicting a target position based on a curvature radius according to claim 1, wherein the fitting of the three projection points by a circular equation or a parabolic equation to obtain a motion curve, and the calculating of the curvature radius of the motion curve at the last projection point specifically comprises:
judging whether the X coordinates of two projection points in the three projection points have equal values or not;
if the three projection points exist, fitting the three projection points through a circular equation to obtain a motion curve, and calculating the curvature radius of the motion curve at the last projection point;
if not, fitting the three projection points by using a parabolic equation to obtain a motion curve, and calculating the curvature radius of the motion curve at the last projection point.
5. The method for predicting the position of a target based on the curvature radius according to claim 1, wherein the step of calculating the instantaneous speed of the target at the last projection point according to the curvature radius is specifically as follows:
calculating an included angle between the normal direction of the motion curve at the last projection point and the gravity direction;
calculating the instantaneous speed of the target at the last projection point according to a first formula, wherein the first formula is mv2Where m is the target mass, v is the instantaneous velocity, r is the radius of curvature, g is the acceleration of gravity, and θ is the angle.
6. The method for predicting a target position based on a curvature radius according to claim 1, wherein the calculating the displacement of the target in the X-axis direction according to the frame interval time and the instantaneous speed is specifically:
calculating an X-axis component of the instantaneous velocity by orthogonal decomposition;
and calculating the displacement of the target in the X-axis direction according to the frame interval time and the X-axis component.
7. The method for predicting the position of an object based on the radius of curvature according to claim 1, wherein the predicted position point of the object passing through the plane is taken as a perpendicular line of an XOY plane, and coordinates of an intersection point of the perpendicular line and the first plane are calculated to obtain the predicted position point of the object, specifically:
drawing a perpendicular line of an XOY plane through the plane prediction point, and calculating an equation of the perpendicular line;
and calculating the coordinates of the intersection point of the perpendicular line and the first plane according to the equation of the perpendicular line and the equation of the first plane to obtain the predicted position point of the target.
8. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the steps of any of claims 1-7.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104835178A (en) * | 2015-02-02 | 2015-08-12 | 郑州轻工业学院 | Low SNR(Signal to Noise Ratio) motion small target tracking and identification method |
| WO2015172679A1 (en) * | 2014-05-14 | 2015-11-19 | 华为技术有限公司 | Image processing method and device |
| CN105701806A (en) * | 2016-01-11 | 2016-06-22 | 上海交通大学 | Depth image-based parkinson's tremor motion characteristic detection method and system |
| CN106875425A (en) * | 2017-01-22 | 2017-06-20 | 北京飞搜科技有限公司 | A kind of multi-target tracking system and implementation method based on deep learning |
| CN108986141A (en) * | 2018-07-03 | 2018-12-11 | 百度在线网络技术（北京）有限公司 | Object of which movement information processing method, device, augmented reality equipment and storage medium |
-
2019
- 2019-06-14 CN CN201910514119.3A patent/CN112085762B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015172679A1 (en) * | 2014-05-14 | 2015-11-19 | 华为技术有限公司 | Image processing method and device |
| CN104835178A (en) * | 2015-02-02 | 2015-08-12 | 郑州轻工业学院 | Low SNR(Signal to Noise Ratio) motion small target tracking and identification method |
| CN105701806A (en) * | 2016-01-11 | 2016-06-22 | 上海交通大学 | Depth image-based parkinson's tremor motion characteristic detection method and system |
| CN106875425A (en) * | 2017-01-22 | 2017-06-20 | 北京飞搜科技有限公司 | A kind of multi-target tracking system and implementation method based on deep learning |
| CN108986141A (en) * | 2018-07-03 | 2018-12-11 | 百度在线网络技术（北京）有限公司 | Object of which movement information processing method, device, augmented reality equipment and storage medium |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112577475A (en) * | 2021-01-14 | 2021-03-30 | 天津希格玛微电子技术有限公司 | Video ranging method capable of effectively reducing power consumption |
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