tracking_KL.cpp

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/* +------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)            |
   |                          https://www.mrpt.org/                         |
   |                                                                        |
   | Copyright (c) 2005-2019, Individual contributors, see AUTHORS file     |
   | See: https://www.mrpt.org/Authors - All rights reserved.               |
   | Released under BSD License. See: https://www.mrpt.org/License          |
   +------------------------------------------------------------------------+ */

#include "vision-precomp.h"  // Precompiled headers

#include <mrpt/system/memory.h>
#include <mrpt/vision/CFeatureExtraction.h>
#include <mrpt/vision/tracking.h>

// Universal include for all versions of OpenCV
#include <mrpt/otherlibs/do_opencv_includes.h>

#if HAVE_ALLOCA_H
#include <alloca.h>
#endif

using namespace mrpt;
using namespace mrpt::vision;
using namespace mrpt::img;
using namespace std;

/** Track a set of features from old_img -> new_img using sparse optimal flow
 *(classic KL method)
 *  Optional parameters that can be passed in "extra_params":
 *      - "window_width"  (Default=15)
 *      - "window_height" (Default=15)
 *
 *  \sa OpenCV's method cvCalcOpticalFlowPyrLK
 */
template <typename FEATLIST>
void CFeatureTracker_KL::trackFeatures_impl_templ(
    const CImage& old_img, const CImage& new_img, FEATLIST& featureList)
{
    MRPT_START

#if MRPT_HAS_OPENCV
    const int window_width = extra_params.getWithDefaultVal("window_width", 15);
    const int window_height =
        extra_params.getWithDefaultVal("window_height", 15);

    const int LK_levels = extra_params.getWithDefaultVal("LK_levels", 3);
    const int LK_max_iters = extra_params.getWithDefaultVal("LK_max_iters", 10);
    const int LK_epsilon = extra_params.getWithDefaultVal("LK_epsilon", 0.1);
    const float LK_max_tracking_error =
        extra_params.getWithDefaultVal("LK_max_tracking_error", 150.0f);

    // Both images must be of the same size
    ASSERT_(
        old_img.getWidth() == new_img.getWidth() &&
        old_img.getHeight() == new_img.getHeight());

    const size_t img_width = old_img.getWidth();
    const size_t img_height = old_img.getHeight();

    const size_t nFeatures = featureList.size();  // Number of features

    // Grayscale images
    const CImage prev_gray(old_img, FAST_REF_OR_CONVERT_TO_GRAY);
    const CImage cur_gray(new_img, FAST_REF_OR_CONVERT_TO_GRAY);

    // Array conversion MRPT->OpenCV
    if (nFeatures > 0)
    {
        std::vector<cv::Point2f> points_prev(nFeatures), points_cur;
        std::vector<uchar> status(nFeatures);
        std::vector<float> track_error(nFeatures);

        for (size_t i = 0; i < nFeatures; ++i)
        {
            points_prev[i].x = featureList.getFeatureX(i);
            points_prev[i].y = featureList.getFeatureY(i);
        }

        const cv::Mat& prev = prev_gray.asCvMatRef();
        const cv::Mat& cur = cur_gray.asCvMatRef();

        cv::calcOpticalFlowPyrLK(
            prev, cur, points_prev, points_cur, status, track_error,
            cv::Size(window_width, window_height), LK_levels,
            cv::TermCriteria(
                cv::TermCriteria::MAX_ITER | cv::TermCriteria::EPS,
                LK_max_iters, LK_epsilon));

        for (size_t i = 0; i < nFeatures; ++i)
        {
            const bool trck_err_too_large =
                track_error[i] > LK_max_tracking_error;

            if (status[i] == 1 && !trck_err_too_large && points_cur[i].x > 0 &&
                points_cur[i].y > 0 && points_cur[i].x < img_width &&
                points_cur[i].y < img_height)
            {
                // Feature could be tracked
                featureList.setFeatureXf(i, points_cur[i].x);
                featureList.setFeatureYf(i, points_cur[i].y);
                featureList.setTrackStatus(i, status_TRACKED);
            }
            else  // Feature could not be tracked
            {
                featureList.setFeatureX(i, -1);
                featureList.setFeatureY(i, -1);
                featureList.setTrackStatus(
                    i, trck_err_too_large ? status_LOST : status_OOB);
            }
        }

        // In case it needs to rebuild a kd-tree or whatever
        featureList.mark_as_outdated();
    }

#else
    THROW_EXCEPTION("The MRPT has been compiled with MRPT_HAS_OPENCV=0 !");
#endif

    MRPT_END
}  // end trackFeatures

void CFeatureTracker_KL::trackFeatures_impl(
    const CImage& old_img, const CImage& new_img, TKeyPointList& featureList)
{
    trackFeatures_impl_templ<TKeyPointList>(old_img, new_img, featureList);
}

void CFeatureTracker_KL::trackFeatures_impl(
    const CImage& old_img, const CImage& new_img, TKeyPointfList& featureList)
{
    trackFeatures_impl_templ<TKeyPointfList>(old_img, new_img, featureList);
}