Patent ID: 11948344
Assignee: WUHAN UNIVERSITY OF TECHNOLOGY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 1:
2. The method for identifying and ranging inland vessels as claimed in claim 1, characterized in that the building of the binocular stereo vision ranging model in Step 1 includes:
the binocular stereo vision ranging technology perceives a depth of a surrounding environment through anthropomorphic methods, and obtains 3D information of targets in a real world; According to the triangulation principle, two parallel and co-planar cameras are used to capture and image a same scene from different angles, and the depth information of the vessel is recovered by calculating the parallax value between the image pairs; an optical center positions of left and right cameras are Ol and Or, respectively, with OlXlYlZl and OrXrYrZr being the coordinate systems of the left and right cameras; b is a horizontal distance between the optical centers Ol and Or of the camera, known as a baseline distance; f is a focal length of the left and the right cameras; For 3D spatial point P(X,Y,Z), a projection point coordinates in the imaging coordinate system of the left and right cameras are p(xl,yl) and p(xr,yr), respectively; project a 3D model onto the XOZ plane; According to a principle of triangle similarity, it can be concluded that:, (
  
   
    
     
      
       
        z
        f
       
       =
       
        x
        
         x
         l
        
       
      
     
    
    
     
      
       
        z
        f
       
       =
       
        
         x
         -
         b
        
        
         x
         r
        
       
      
     
    
    
     
      
       
        z
        f
       
       =
       
        
         y
         
          y
          l
         
        
        =
        
         y
         
          y
          r
         
        
       
      
     
    
   
   ;
  
 

a calculation leads to:, (
  
   
    
     
      
       z
       =
       
        
         
          f
          *
          b
         
         
          
           x
           l
          
          -
          
           x
           r
          
         
        
        =
        
         
          f
          *
          b
         
         d
        
       
      
     
    
    
     
      
       x
       =
       
        
         
          x
          l
         
         *
         z
        
        f
       
      
     
    
    
     
      
       f
       =
       
        
         
          
           
            y
            l
           
           *
           z
          
          f
         
         ⁢
            
         or
         ⁢
            
         f
        
        =
        
         
          
           y
           r
          
          *
          z
         
         f
        
       
      
     
    
   
   ;
  
 

Where, xl−xr is called parallax d, which represents an offset of point P from the corresponding projection point on the left and right cameras; z is a depth value of point P; When parameters f and b are determined, a depth z of a target point is obtained by calculating a difference between the coordinates x or y of the target point in a pixel coordinate system of the left and right cameras;
calculate the projection point coordinates pl(xl,yl) and pr(xr,yr) of the point on the left and right camera imaging planes, and obtain a 3D information of the point through a transformation between coordinate systems, thereby obtaining the depth information of the target point P;
the building of a camera calibration model in Step 2 includes:
According to a principle of pinhole imaging, when a point Pw(Xw,Yw,Zw) is located in a 3D world coordinate system, the projection coordinate of the point in a camera coordinate system is Pc(Xc,Yc,Zc), the coordinate in an image coordinate system is P(x,y), pixel coordinates P(u,v), and Oc in the pixel coordinate system are the camera optical center position, and OcZc is the camera optical axis of the left and right cameras; a mathematical expression between Pw(Xw,Yw,Zw) and the pixel coordinate P(u,v) is:, Z
        c
       
       (
       
        
         
          u
         
        
        
         
          v
         
        
        
         
          1
         
        
       
       )
      
      =
      
       
        (
        
         
          
           
            1
            dx
           
          
          
           0
          
          
           
            u
            0
           
          
         
         
          
           0
          
          
           
            1
            dy
           
          
          
           
            v
            0
           
          
         
         
          
           0
          
          
           0
          
          
           1
          
         
        
        )
       
       ⁢
       
        (
        
         
          
           f
          
          
           0
          
          
           0
          
          
           0
          
         
         
          
           0
          
          
           f
          
          
           0
          
          
           0
          
         
         
          
           0
          
          
           f
          
          
           0
          
          
           0
          
         
        
        )
       
       ⁢
       
        (
        
         
          
           R
          
          
           T
          
         
         
          
           
            0
            →
           
          
          
           1
          
         
        
        )
       
       ⁢
       
        (
        
         
          
           
            X
            w
           
          
         
         
          
           
            Y
            w
           
          
         
         
          
           
            Z
            w
           
          
         
         
          
           1
          
         
        
        )
       
      
     
    
   
   
    
     
      =
      
       
        (
        
         
          
           
            f
            x
           
          
          
           0
          
          
           
            u
            0
           
          
          
           0
          
         
         
          
           0
          
          
           
            f
            y
           
          
          
           
            v
            0
           
          
          
           0
          
         
         
          
           0
          
          
           0
          
          
           1
          
          
           0
          
         
        
        )
       
       ⁢
       
        (
        
         
          
           R
          
          
           T
          
         
         
          
           
            0
            →
           
          
          
           1
          
         
        
        )
       
       ⁢
       
        (
        
         
          
           
            X
            w
           
          
         
         
          
           
            Y
            w
           
          
         
         
          
           
            Z
            w
           
          
         
         
          
           1
          
         
        
        )
       
      
     
    
   
  
  ;, Let, K
   =
   
    (
    
     
      
       
        f
        x
       
      
      
       0
      
      
       
        u
        0
       
      
      
       0
      
     
     
      
       0
      
      
       
        f
        y
       
      
      
       
        v
        0
       
      
      
       0
      
     
     
      
       0
      
      
       0
      
      
       1
      
      
       0
      
     
    
    )
   
  
  ,, referred to as an internal parameter matrix of the left and right cameras, then a mathematical expression between Pw(Xw,Yw,Zw) and the pixel coordinate P(u,v) is simplified as follows:, Z
     c
    
    (
    
     
      
       u
      
     
     
      
       v
      
     
     
      
       1
      
     
    
    )
   
   =
   
    
     K
     ⁡
     (
     
      
       
        R
       
       
        T
       
      
      
       
        
         0
         →
        
       
       
        1
       
      
     
     )
    
    ⁢
    
     (
     
      
       
        
         X
         w
        
       
      
      
       
        
         Y
         w
        
       
      
      
       
        
         Z
         w
        
       
      
      
       
        1
       
      
     
     )
    
   
  
  ;
 

Where,, f
    x
   
   =
   
    f
    
     d
     x
    
   
  
  ,
  
   
    f
    y
   
   =
   
    f
    
     d
     y
    
   
  
  ,
  
   
    d
    x
   
   ⁢
      
   and
   ⁢
      
   
    d
    y
   
  
 

 respectively represent physical dimensions of each pixel in the x and y directions of the image plane, u0 and v0 represent the coordinates of the image center point, R represents the rotation matrix, and T represents a translation vector, which constitute an external parameter matrix, (
  
   
    
     R
    
    
     T
    
   
   
    
     
      0
      →
     
    
    
     1
    
   
  
  )
 

 of the camera, and the external parameter matrix and internal parameter matrix of the left and right cameras can be obtained by the camera calibration.