Transform front-facing camera image into top-down view
System object™ warps a front-facing camera image into a top-down view. It uses a
hardware-efficient architecture that supports HDL code generation.
You must provide the homography matrix that describes the transform. This matrix can be calculated from physical camera properties, or empirically derived by analyzing an image of a grid pattern taken by the camera. The object uses the matrix to compute the transformed coordinates of each pixel. The transform does not interpolate between pixel locations. Instead it rounds the result to the nearest coordinate.
The object operates on a trapezoidal region of the input image below the vanishing point. These images show the input region selected for transformation and the resulting top-down view.
You can specify the number of lines in the transformed region and the size of the output frame. If the specified homography matrix cannot map from the requested number of lines to the requested output size, the object returns a warning.
Because the object replicates lines from the input region to create the larger output frame, it cannot complete the transform of one frame before the next frame arrives. The object ignores any new input frames while it is still transforming the previous frame. Therefore, depending on the stored lines and output size, the object can drop input frames. This timing also enables the object to maintain the blanking intervals of the input pixel stream.
To transform a front-facing camera image to top-down view:
visionhdl.BirdsEyeViewobject and set its properties.
Call the object with arguments, as if it were a function.
To learn more about how System objects work, see What Are System Objects?
birdsEyeXfrm = visionhdl.BirdsEyeView(
returns a bird's-eye transform System object, with the homography matrix set to
hM, and a buffer
MaxBufferSize pixels. You can optionally set additional
properties using name-value pairs. Enclose each property name in single quotes.
Unless otherwise indicated, properties are nontunable, which means you cannot change their
values after calling the object. Objects lock when you call them, and the
release function unlocks them.
If a property is tunable, you can change its value at any time.
For more information on changing property values, see System Design in MATLAB Using System Objects.
HomographyMatrix — Transfer function derived from camera parameters
[0.000100990123328 0 0;0.000412396945637 0.001302203393162
-0.000222053779501] (default) | 3-by-3 matrix
Transfer function derived from camera parameters, specified as a 3-by-3 matrix.
The homography matrix, h, is derived from four intrinsic parameters of the physical camera setup: the focal length, pitch, height, and principal point (from a pinhole camera model). The default value is the matrix for the camera setup used in the Lane Detection example.
This matrix can be calculated from physical camera properties, or empirically
derived by analyzing an image of a grid test pattern taken by the camera. See
estimateGeometricTransform (Computer Vision Toolbox) or Using the Single Camera Calibrator App (Computer Vision Toolbox).
MaxBufferSize — Number of input pixels to buffer
40000 (default) | integer
Number of input pixels to buffer, specified as an integer. Compute this value from
The object uses a memory of this size to store the input pixels. If you specify a value
that is not a power of two, the object uses the next largest power of two.
MaxSourceLinesBuffered — Number of lines to transform
54 (default) | integer
Number of lines to transform, specified as an integer. The object stores and
transforms this number of lines into the output bird's-eye view image, starting at the
vanishing point as determined by the
Storing the full input frame uses too much memory to implement the algorithm without off-chip storage. Therefore, for a hardware implementation, choose a smaller region to store and transform, one that generates an acceptable output frame size.
For example, using the default
HomographyMatrix with an input
image of 640-by-480 pixels, the full-sized transform results in a 900-by-640 output
image. Analysis of the input-to-output x-coordinate mapping shows
that around 50 lines of the input image are required to generate the top 700 lines of
the bird's-eye view output image. This number of input lines can be stored using on-chip
memory. The vanishing point for the default camera setup is around line 200, and lines
above that point do not contribute to the resulting bird's-eye view. Therefore, the
object can store only input lines 200–250 for transformation.
BirdEyeActivePixels — Horizontal size of output frame
640 (default) | integer
Horizontal size of output frame, specified as an integer. This parameter is the number of active pixels in each output line.
BirdEyeActiveLines — Vertical size of output frame
700 (default) | integer
Vertical size of output frame, specified as an integer. This parameter is the number of active lines in each output frame.
returns the bird's-eye view transformation of the input stream. The frame size of the
output stream corresponds to the size you configured in the
ctrlout] = birdsEyeXfrm(
This object uses a streaming pixel interface with a structure
for frame control signals. This interface enables the object to operate independently of image
size and format and to connect with other Vision HDL Toolbox™ objects. The object accepts and returns a scalar pixel value and control signals
as a structure containing five signals. The control signals indicate the validity of each pixel
and its location in the frame. To convert a pixel matrix into a pixel stream and control
signals, use the
visionhdl.FrameToPixels object. For a
description of the interface, see Streaming Pixel Interface.
pixelin — Input pixel stream
Single image pixel in a pixel stream, specified as a scalar value representing intensity.
types are supported for simulation, but not for HDL code generation.
pixelout — Output pixel stream
Single image pixel in a pixel stream, returned as a scalar value representing intensity.
single data types are supported for simulation, but not for HDL
To use an object function, specify the
System object as the first input argument. For
example, to release system resources of a System object named
The transform from input pixel coordinate (x,y) to the bird's-eye pixel coordinate is derived from the homography matrix, h. The homography matrix is based on physical parameters and therefore is a constant for a particular camera installation.
The implementation of the bird's-eye transform in hardware does not directly perform this calculation. Instead, the object precomputes lookup tables for the horizontal and vertical aspects of the transform.
First, the object stores the input lines starting from the precomputed vanishing point.
The stored pixels form a trapezoid, with short lines near the vanishing point and wider lines
near the camera. This storage uses
MaxBufferSize memory locations.
The horizontal lookup table contains interpolation parameters that describe the stretch of each line of the trapezoidal input region to the requested width of the output frame. Lines that fall closer to the vanishing point are stretched more than lines nearer to the camera.
The vertical lookup table contains the y-coordinate mapping, and how many times each line is repeated to fill the requested height of the output frame. Near the vanishing point, one input line maps to many output lines, while each line nearer the camera maps to a diminishing number of output lines.
The lookup tables use 3*
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
This System object supports C/C++ code generation for accelerating MATLAB® simulations, and for DPI component generation. For more information about acceleration, see Accelerate Pixel-Streaming Designs Using MATLAB Coder. For more information about DPI component generation, see Considerations for DPI Component Generation with MATLAB (HDL Verifier).
HDL Code Generation
Generate Verilog and VHDL code for FPGA and ASIC designs using HDL Coder™.
To generate HDL code from Vision HDL Toolbox System objects, see Design Hardware-Targeted Image Filters in MATLAB.
Introduced in R2017b