Пример #1
0
        /// <summary>
        /// Create a visible color shaded image of a point cloud and its normals with simple
        /// grayscale L.N surface shading. All image frames must have the same width and height.
        /// </summary>
        /// <param name="pointCloudFrame">The point cloud frame to be shaded.</param>
        /// <param name="worldToCameraTransform">
        /// The world to camera transform (camera pose) where the raycast was performed from.
        /// Pass identity if the point cloud did not originate from a raycast and is in the
        /// camera local coordinate system.
        /// </param>
        /// <param name="shadedSurfaceFrame">
        /// Optionally, a pre-allocated color image frame, to be filled with the grayscale L.N
        /// shaded surface image. Pass null to skip this image.
        /// </param>
        /// <param name="shadedSurfaceNormalsFrame">
        /// Optionally, a pre-allocated color image frame, to be filled with the color shaded
        /// normals image with color indicating orientation. Pass null to skip this image.
        /// </param>
        /// <exception cref="ArgumentNullException">
        /// Thrown when the <paramref name="pointCloudFrame"/> parameter is null.
        /// </exception>
        /// <exception cref="ArgumentException">
        /// Thrown when the <paramref name="pointCloudFrame"/> or <paramref name="shadedSurfaceFrame"/>
        /// or <paramref name="shadedSurfaceNormalsFrame"/> parameters are different image sizes.
        /// Thrown when the <paramref name="pointCloudFrame"/> or <paramref name="shadedSurfaceFrame"/>
        /// or <paramref name="shadedSurfaceNormalsFrame"/> parameters have different camera parameters.
        /// </exception>
        /// <exception cref="OutOfMemoryException">
        /// Thrown if a CPU memory allocation failed.
        /// </exception>
        /// <exception cref="InvalidOperationException">
        /// Thrown when the Kinect Runtime could not be accessed, the device is not connected,
        /// a GPU memory allocation failed or the call failed for an unknown reason.
        /// </exception>
        public static void ShadePointCloud(
            FusionPointCloudImageFrame pointCloudFrame,
            Matrix4 worldToCameraTransform,
            FusionColorImageFrame shadedSurfaceFrame,
            FusionColorImageFrame shadedSurfaceNormalsFrame)
        {
            if (null == pointCloudFrame)
            {
                throw new ArgumentNullException("pointCloudFrame");
            }

            ExceptionHelper.ThrowIfFailed(NativeMethods.NuiFusionShadePointCloud2(
                                              FusionImageFrame.ToHandleRef(pointCloudFrame),
                                              ref worldToCameraTransform,
                                              IntPtr.Zero,
                                              FusionImageFrame.ToHandleRef(shadedSurfaceFrame),
                                              FusionImageFrame.ToHandleRef(shadedSurfaceNormalsFrame)));
        }
Пример #2
0
        /// <summary>
        /// Find the most similar camera poses to the current camera input by comparing against the
        /// camera pose finder database, and returning a set of similar camera poses. These poses
        /// and similarity measurements are ordered in terms of decreasing similarity (i.e. the most
        /// similar is first). Both input depth and color frames must be identical sizes, with valid
        /// camera parameters and captured at the same time.
        /// </summary>
        /// <param name="depthFloatFrame">The depth float frame to be processed.</param>
        /// <param name="colorFrame">The color frame to be processed.</param>
        /// <returns>Returns the matched frames object created by the camera pose finder.</returns>
        /// <exception cref="ArgumentNullException">
        /// Thrown when the <paramref name="depthFloatFrame"/> or <paramref name="colorFrame"/>
        /// parameter is null. </exception>
        /// <exception cref="ArgumentException">
        /// Thrown when the <paramref name="depthFloatFrame"/> and  <paramref name="colorFrame"/>
        /// parameter is an incorrect or different image size, or their <c>CameraParameters</c>
        /// member is null or has incorrectly sized focal lengths.</exception>
        /// <exception cref="InvalidOperationException">
        /// Thrown when the Kinect Runtime could not be accessed,
        /// or the call failed for an unknown reason.
        /// </exception>
        /// <returns>Returns a set of matched frames/poses.</returns>
        public MatchCandidates FindCameraPose(
            FusionFloatImageFrame depthFloatFrame,
            FusionColorImageFrame colorFrame)
        {
            if (null == depthFloatFrame)
            {
                throw new ArgumentNullException("depthFloatFrame");
            }

            if (null == colorFrame)
            {
                throw new ArgumentNullException("colorFrame");
            }

            INuiFusionMatchCandidates matchCandidates = null;

            ExceptionHelper.ThrowIfFailed(cameraPoseFinder.FindCameraPose(
                                              FusionImageFrame.ToHandleRef(depthFloatFrame),
                                              FusionImageFrame.ToHandleRef(colorFrame),
                                              out matchCandidates));

            return(new MatchCandidates(matchCandidates));
        }
Пример #3
0
        /// <summary>
        /// The AlignPointClouds function uses an iterative algorithm to align two sets of oriented
        /// point clouds and calculate the camera's relative pose. This is a generic function which
        /// can be used independently of a Reconstruction Volume with sets of overlapping point clouds.
        /// All images must be the same size and have the same camera parameters.
        /// To find the frame-to-frame relative transformation between two sets of point clouds in
        /// the camera local frame of reference (created by DepthFloatFrameToPointCloud),
        /// set the <paramref name="observedToReferenceTransform"/> to the identity.
        /// To calculate the frame-to-model pose transformation between point clouds calculated from
        /// new depth frames with DepthFloatFrameToPointCloud and point clouds calculated from an
        /// existing Reconstruction volume with CalculatePointCloud (e.g. from the previous frame),
        /// pass the CalculatePointCloud image as the reference frame, and the current depth frame
        /// point cloud from DepthFloatFrameToPointCloud as the observed frame. Set the
        /// <paramref name="observedToReferenceTransform"/> to the previous frames calculated camera
        /// pose that was used in the CalculatePointCloud call.
        /// Note that here the current frame point cloud will be in the camera local frame of
        /// reference, whereas the raycast points and normals will be in the global/world coordinate
        /// system. By passing the <paramref name="observedToReferenceTransform"/> you make the
        /// algorithm aware of the transformation between the two coordinate systems.
        /// The <paramref name="observedToReferenceTransform"/> pose supplied can also take into
        /// account information you may have from other sensors or sensing mechanisms to aid the
        /// tracking. To do this multiply the relative frame to frame delta transformation from
        /// the other sensing system with the previous frame's pose before passing to this function.
        /// Note that any delta transform used should be in the same coordinate system as that
        /// returned by the DepthFloatFrameToPointCloud calculation.
        /// </summary>
        /// <param name="referencePointCloudFrame">
        /// The point cloud frame of the reference camera, or the previous Kinect point cloud frame.
        /// </param>
        /// <param name="observedPointCloudFrame">
        /// The point cloud frame of the observed camera, or the current Kinect frame.
        /// </param>
        /// <param name="maxAlignIterationCount">
        /// The maximum number of iterations of the algorithm to run. The minimum value is 1.
        /// Using only a small number of iterations will have a faster runtime, however, the
        /// algorithm may not converge to the correct transformation.
        /// </param>
        /// <param name="deltaFromReferenceFrame">
        /// Optionally, a pre-allocated color image frame, to be filled with color-coded data
        /// from the camera tracking. This may be used as input to additional vision algorithms such as
        /// object segmentation. Values vary depending on whether the pixel was a valid pixel used in
        /// tracking (inlier) or failed in different tests (outlier). 0xff000000 indicates an invalid
        /// input vertex (e.g. from 0 input depth), or one where no correspondences occur between point
        /// cloud images. Outlier vertices rejected due to too large a distance between vertices are
        /// coded as 0xff008000. Outlier vertices rejected due to to large a difference in normal angle
        /// between point clouds are coded as 0xff800000. Inliers are color shaded depending on the
        /// residual energy at that point, with more saturated colors indicating more discrepancy
        /// between vertices and less saturated colors (i.e. more white) representing less discrepancy,
        /// or less information at that pixel. Pass null if this image is not required.
        /// </param>
        /// <param name="observedToReferenceTransform">
        /// A pre-allocated transformation matrix. At entry to the function this should be filled
        /// with the best guess for the observed to reference transform (usually the last frame's
        /// calculated pose). At exit this is filled with he calculated pose or identity if the
        /// calculation failed.
        /// </param>
        /// <returns>
        /// Returns true if successful; returns false if the algorithm encountered a problem aligning
        /// the input point clouds and could not calculate a valid transformation, and
        /// the <paramref name="observedToReferenceTransform"/> parameter is set to identity.
        /// </returns>
        /// <exception cref="ArgumentNullException">
        /// Thrown when the <paramref name="referencePointCloudFrame"/> or the
        /// <paramref name="observedPointCloudFrame"/> parameter is null.
        /// </exception>
        /// <exception cref="ArgumentException">
        /// Thrown when the <paramref name="referencePointCloudFrame"/> or <paramref name="observedPointCloudFrame"/>
        /// or <paramref name="deltaFromReferenceFrame"/> parameters are different image sizes.
        /// Thrown when the <paramref name="referencePointCloudFrame"/> or <paramref name="observedPointCloudFrame"/>
        /// or <paramref name="deltaFromReferenceFrame"/> parameters have different camera parameters.
        /// Thrown when the <paramref name="maxAlignIterationCount"/> parameter is less than 1.
        /// </exception>
        /// <exception cref="OutOfMemoryException">
        /// Thrown if a CPU memory allocation failed.
        /// </exception>
        /// <exception cref="InvalidOperationException">
        /// Thrown when the Kinect Runtime could not be accessed, the device is not connected,
        /// a GPU memory allocation failed or the call failed for an unknown reason.
        /// </exception>
        public static bool AlignPointClouds(
            FusionPointCloudImageFrame referencePointCloudFrame,
            FusionPointCloudImageFrame observedPointCloudFrame,
            int maxAlignIterationCount,
            FusionColorImageFrame deltaFromReferenceFrame,
            ref Matrix4 observedToReferenceTransform)
        {
            if (null == referencePointCloudFrame)
            {
                throw new ArgumentNullException("referencePointCloudFrame");
            }

            if (null == observedPointCloudFrame)
            {
                throw new ArgumentNullException("observedPointCloudFrame");
            }

            ushort maxIterations = ExceptionHelper.CastAndThrowIfOutOfUshortRange(maxAlignIterationCount);

            HRESULT hr = NativeMethods.NuiFusionAlignPointClouds(
                FusionImageFrame.ToHandleRef(referencePointCloudFrame),
                FusionImageFrame.ToHandleRef(observedPointCloudFrame),
                maxIterations,
                FusionImageFrame.ToHandleRef(deltaFromReferenceFrame),
                ref observedToReferenceTransform);

            if (hr == HRESULT.E_NUI_FUSION_TRACKING_ERROR)
            {
                return(false);
            }
            else
            {
                ExceptionHelper.ThrowIfFailed(hr);
            }

            return(true);
        }