COMPMID-344 Updated doxygen
Change-Id: I32f7b84daa560e460b77216add529c8fa8b327ae
diff --git a/src/core/NEON/kernels/NELKTrackerKernel.cpp b/src/core/NEON/kernels/NELKTrackerKernel.cpp
new file mode 100644
index 0000000..3d2bfb2
--- /dev/null
+++ b/src/core/NEON/kernels/NELKTrackerKernel.cpp
@@ -0,0 +1,533 @@
+/*
+ * Copyright (c) 2016, 2017 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/core/NEON/kernels/NELKTrackerKernel.h"
+
+#include "arm_compute/core/AccessWindowStatic.h"
+#include "arm_compute/core/Coordinates.h"
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/Window.h"
+
+#include <arm_neon.h>
+#include <cmath>
+
+using namespace arm_compute;
+
+/** Constants used for Lucas-Kanade Algorithm */
+constexpr int W_BITS = 14;
+constexpr float D0 = 1 << W_BITS;
+constexpr float DETERMINANT_THRESHOLD = 1.0e-07f; // Threshold for the determinant. Used for lost tracking criteria
+constexpr float EIGENVALUE_THRESHOLD = 1.0e-04f; // Thresholds for minimum eigenvalue. Used for lost tracking criteria
+constexpr float FLT_SCALE = 1.0f / (1 << 20);
+
+namespace
+{
+enum class BilinearInterpolation
+{
+ BILINEAR_OLD_NEW,
+ BILINEAR_SCHARR
+};
+
+template <typename T>
+constexpr int INT_ROUND(T x, int n)
+{
+ return (x + (1 << (n - 1))) >> n;
+}
+
+template <typename T>
+inline int get_pixel(const ITensor *tensor, int xi, int yi, int iw00, int iw01, int iw10, int iw11, int scale)
+{
+ const auto px00 = *reinterpret_cast<const T *>(tensor->buffer() + tensor->info()->offset_element_in_bytes(Coordinates(xi, yi)));
+ const auto px01 = *reinterpret_cast<const T *>(tensor->buffer() + tensor->info()->offset_element_in_bytes(Coordinates(xi + 1, yi)));
+ const auto px10 = *reinterpret_cast<const T *>(tensor->buffer() + tensor->info()->offset_element_in_bytes(Coordinates(xi, yi + 1)));
+ const auto px11 = *reinterpret_cast<const T *>(tensor->buffer() + tensor->info()->offset_element_in_bytes(Coordinates(xi + 1, yi + 1)));
+
+ return INT_ROUND(px00 * iw00 + px01 * iw01 + px10 * iw10 + px11 * iw11, scale);
+}
+
+inline int32x4_t compute_bilinear_interpolation(int16x8_t top_row, int16x8_t bottom_row, int16x4_t w00, int16x4_t w01, int16x4_t w10, int16x4_t w11, int32x4_t shift)
+{
+ // Get the left column of upper row
+ const int16x4_t px00 = vget_low_s16(top_row);
+
+ // Get the right column of upper row
+ const int16x4_t px01 = vext_s16(px00, vget_high_s16(top_row), 1);
+
+ // Get the left column of lower row
+ const int16x4_t px10 = vget_low_s16(bottom_row);
+
+ // Get the right column of right row
+ const int16x4_t px11 = vext_s16(px10, vget_high_s16(bottom_row), 1);
+
+ // Apply the bilinear filter
+ return vqrshlq_s32(vmull_s16(px00, w00) + vmull_s16(px01, w01) + vmull_s16(px10, w10) + vmull_s16(px11, w11), shift);
+}
+} // namespace
+
+void NELKTrackerKernel::init_keypoints(int start, int end)
+{
+ if(_level == _num_levels - 1)
+ {
+ const float level_scale = pow(_pyramid_scale, _level);
+
+ for(int i = start; i < end; ++i)
+ {
+ _old_points_internal->at(i).x = _old_points->at(i).x * level_scale;
+ _old_points_internal->at(i).y = _old_points->at(i).y * level_scale;
+ _old_points_internal->at(i).tracking_status = true;
+
+ NELKInternalKeypoint keypoint_to_track;
+
+ if(_use_initial_estimate)
+ {
+ keypoint_to_track.x = _new_points_estimates->at(i).x * level_scale;
+ keypoint_to_track.y = _new_points_estimates->at(i).y * level_scale;
+ keypoint_to_track.tracking_status = (_new_points_estimates->at(i).tracking_status == 1);
+ }
+ else
+ {
+ keypoint_to_track.x = _old_points_internal->at(i).x;
+ keypoint_to_track.y = _old_points_internal->at(i).y;
+ keypoint_to_track.tracking_status = true;
+ }
+
+ _new_points_internal->at(i) = keypoint_to_track;
+ }
+ }
+ else
+ {
+ for(int i = start; i < end; ++i)
+ {
+ _old_points_internal->at(i).x /= _pyramid_scale;
+ _old_points_internal->at(i).y /= _pyramid_scale;
+ _new_points_internal->at(i).x /= _pyramid_scale;
+ _new_points_internal->at(i).y /= _pyramid_scale;
+ }
+ }
+}
+
+std::tuple<int, int, int> NELKTrackerKernel::compute_spatial_gradient_matrix(const NELKInternalKeypoint &keypoint, int *bilinear_ix, int *bilinear_iy)
+{
+ int iA11 = 0;
+ int iA12 = 0;
+ int iA22 = 0;
+
+ int32x4_t nA11 = vdupq_n_s32(0);
+ int32x4_t nA12 = vdupq_n_s32(0);
+ int32x4_t nA22 = vdupq_n_s32(0);
+
+ float keypoint_int_x = 0;
+ float keypoint_int_y = 0;
+
+ const float wx = std::modf(keypoint.x, &keypoint_int_x);
+ const float wy = std::modf(keypoint.y, &keypoint_int_y);
+
+ const int iw00 = roundf((1.0f - wx) * (1.0f - wy) * D0);
+ const int iw01 = roundf(wx * (1.0f - wy) * D0);
+ const int iw10 = roundf((1.0f - wx) * wy * D0);
+ const int iw11 = D0 - iw00 - iw01 - iw10;
+
+ const int16x4_t nw00 = vdup_n_s16(iw00);
+ const int16x4_t nw01 = vdup_n_s16(iw01);
+ const int16x4_t nw10 = vdup_n_s16(iw10);
+ const int16x4_t nw11 = vdup_n_s16(iw11);
+
+ // Convert stride from uint_t* to int16_t*
+ const size_t row_stride = _old_scharr_gx->info()->strides_in_bytes()[1] / 2;
+ const Coordinates top_left_window_corner(static_cast<int>(keypoint_int_x) - _window_dimension / 2, static_cast<int>(keypoint_int_y) - _window_dimension / 2);
+ auto idx = reinterpret_cast<const int16_t *>(_old_scharr_gx->buffer() + _old_scharr_gx->info()->offset_element_in_bytes(top_left_window_corner));
+ auto idy = reinterpret_cast<const int16_t *>(_old_scharr_gy->buffer() + _old_scharr_gy->info()->offset_element_in_bytes(top_left_window_corner));
+ static const int32x4_t nshifter_scharr = vdupq_n_s32(-W_BITS);
+
+ for(int ky = 0; ky < _window_dimension; ++ky, idx += row_stride, idy += row_stride)
+ {
+ int kx = 0;
+
+ // Calculate elements in blocks of four as long as possible
+ for(; kx <= _window_dimension - 4; kx += 4)
+ {
+ // Interpolation X
+ const int16x8_t ndx_row1 = vld1q_s16(idx + kx);
+ const int16x8_t ndx_row2 = vld1q_s16(idx + kx + row_stride);
+
+ const int32x4_t nxval = compute_bilinear_interpolation(ndx_row1, ndx_row2, nw00, nw01, nw10, nw11, nshifter_scharr);
+
+ // Interpolation Y
+ const int16x8_t ndy_row1 = vld1q_s16(idy + kx);
+ const int16x8_t ndy_row2 = vld1q_s16(idy + kx + row_stride);
+
+ const int32x4_t nyval = compute_bilinear_interpolation(ndy_row1, ndy_row2, nw00, nw01, nw10, nw11, nshifter_scharr);
+
+ // Store the intermediate data so that we don't need to recalculate them in later stage
+ vst1q_s32(bilinear_ix + kx + ky * _window_dimension, nxval);
+ vst1q_s32(bilinear_iy + kx + ky * _window_dimension, nyval);
+
+ // Accumulate Ix^2
+ nA11 = vmlaq_s32(nA11, nxval, nxval);
+ // Accumulate Ix * Iy
+ nA12 = vmlaq_s32(nA12, nxval, nyval);
+ // Accumulate Iy^2
+ nA22 = vmlaq_s32(nA22, nyval, nyval);
+ }
+
+ // Calculate the leftover elements
+ for(; kx < _window_dimension; ++kx)
+ {
+ const int32_t ixval = get_pixel<int16_t>(_old_scharr_gx, top_left_window_corner.x() + kx, top_left_window_corner.y() + ky,
+ iw00, iw01, iw10, iw11, W_BITS);
+ const int32_t iyval = get_pixel<int16_t>(_old_scharr_gy, top_left_window_corner.x() + kx, top_left_window_corner.y() + ky,
+ iw00, iw01, iw10, iw11, W_BITS);
+
+ iA11 += ixval * ixval;
+ iA12 += ixval * iyval;
+ iA22 += iyval * iyval;
+
+ bilinear_ix[kx + ky * _window_dimension] = ixval;
+ bilinear_iy[kx + ky * _window_dimension] = iyval;
+ }
+ }
+
+ iA11 += vgetq_lane_s32(nA11, 0) + vgetq_lane_s32(nA11, 1) + vgetq_lane_s32(nA11, 2) + vgetq_lane_s32(nA11, 3);
+ iA12 += vgetq_lane_s32(nA12, 0) + vgetq_lane_s32(nA12, 1) + vgetq_lane_s32(nA12, 2) + vgetq_lane_s32(nA12, 3);
+ iA22 += vgetq_lane_s32(nA22, 0) + vgetq_lane_s32(nA22, 1) + vgetq_lane_s32(nA22, 2) + vgetq_lane_s32(nA22, 3);
+
+ return std::make_tuple(iA11, iA12, iA22);
+}
+
+std::pair<int, int> NELKTrackerKernel::compute_image_mismatch_vector(const NELKInternalKeypoint &old_keypoint, const NELKInternalKeypoint &new_keypoint, const int *bilinear_ix, const int *bilinear_iy)
+{
+ int ib1 = 0;
+ int ib2 = 0;
+
+ int32x4_t nb1 = vdupq_n_s32(0);
+ int32x4_t nb2 = vdupq_n_s32(0);
+
+ // Compute weights for the old keypoint
+ float old_keypoint_int_x = 0;
+ float old_keypoint_int_y = 0;
+
+ const float old_wx = std::modf(old_keypoint.x, &old_keypoint_int_x);
+ const float old_wy = std::modf(old_keypoint.y, &old_keypoint_int_y);
+
+ const int iw00_old = roundf((1.0f - old_wx) * (1.0f - old_wy) * D0);
+ const int iw01_old = roundf(old_wx * (1.0f - old_wy) * D0);
+ const int iw10_old = roundf((1.0f - old_wx) * old_wy * D0);
+ const int iw11_old = D0 - iw00_old - iw01_old - iw10_old;
+
+ const int16x4_t nw00_old = vdup_n_s16(iw00_old);
+ const int16x4_t nw01_old = vdup_n_s16(iw01_old);
+ const int16x4_t nw10_old = vdup_n_s16(iw10_old);
+ const int16x4_t nw11_old = vdup_n_s16(iw11_old);
+
+ // Compute weights for the new keypoint
+ float new_keypoint_int_x = 0;
+ float new_keypoint_int_y = 0;
+
+ const float new_wx = std::modf(new_keypoint.x, &new_keypoint_int_x);
+ const float new_wy = std::modf(new_keypoint.y, &new_keypoint_int_y);
+
+ const int iw00_new = roundf((1.0f - new_wx) * (1.0f - new_wy) * D0);
+ const int iw01_new = roundf(new_wx * (1.0f - new_wy) * D0);
+ const int iw10_new = roundf((1.0f - new_wx) * new_wy * D0);
+ const int iw11_new = D0 - iw00_new - iw01_new - iw10_new;
+
+ const int16x4_t nw00_new = vdup_n_s16(iw00_new);
+ const int16x4_t nw01_new = vdup_n_s16(iw01_new);
+ const int16x4_t nw10_new = vdup_n_s16(iw10_new);
+ const int16x4_t nw11_new = vdup_n_s16(iw11_new);
+
+ const int row_stride = _input_new->info()->strides_in_bytes()[1];
+ const Coordinates top_left_window_corner_old(static_cast<int>(old_keypoint_int_x) - _window_dimension / 2, static_cast<int>(old_keypoint_int_y) - _window_dimension / 2);
+ const Coordinates top_left_window_corner_new(static_cast<int>(new_keypoint_int_x) - _window_dimension / 2, static_cast<int>(new_keypoint_int_y) - _window_dimension / 2);
+ const uint8_t *old_ptr = _input_old->buffer() + _input_old->info()->offset_element_in_bytes(top_left_window_corner_old);
+ const uint8_t *new_ptr = _input_new->buffer() + _input_new->info()->offset_element_in_bytes(top_left_window_corner_new);
+ static const int32x4_t nshifter_tensor = vdupq_n_s32(-(W_BITS - 5));
+
+ for(int ky = 0; ky < _window_dimension; ++ky, new_ptr += row_stride, old_ptr += row_stride)
+ {
+ int kx = 0;
+
+ // Calculate elements in blocks of four as long as possible
+ for(; kx <= _window_dimension - 4; kx += 4)
+ {
+ // Interpolation old tensor
+ const int16x8_t nold_row1 = vreinterpretq_s16_u16(vmovl_u8(vld1_u8(old_ptr + kx)));
+ const int16x8_t nold_row2 = vreinterpretq_s16_u16(vmovl_u8(vld1_u8(old_ptr + kx + row_stride)));
+
+ const int32x4_t noldval = compute_bilinear_interpolation(nold_row1, nold_row2, nw00_old, nw01_old, nw10_old, nw11_old, nshifter_tensor);
+
+ // Interpolation new tensor
+ const int16x8_t nnew_row1 = vreinterpretq_s16_u16(vmovl_u8(vld1_u8(new_ptr + kx)));
+ const int16x8_t nnew_row2 = vreinterpretq_s16_u16(vmovl_u8(vld1_u8(new_ptr + kx + row_stride)));
+
+ const int32x4_t nnewval = compute_bilinear_interpolation(nnew_row1, nnew_row2, nw00_new, nw01_new, nw10_new, nw11_new, nshifter_tensor);
+
+ // Calculate It gradient, i.e. pixelwise difference between old and new tensor
+ const int32x4_t diff = vsubq_s32(nnewval, noldval);
+
+ // Load the Ix and Iy gradient computed in the previous stage
+ const int32x4_t nxval = vld1q_s32(bilinear_ix + kx + ky * _window_dimension);
+ const int32x4_t nyval = vld1q_s32(bilinear_iy + kx + ky * _window_dimension);
+
+ // Caculate Ix * It and Iy * It, and accumulate the results
+ nb1 = vmlaq_s32(nb1, diff, nxval);
+ nb2 = vmlaq_s32(nb2, diff, nyval);
+ }
+
+ // Calculate the leftover elements
+ for(; kx < _window_dimension; ++kx)
+ {
+ const int32_t ival = get_pixel<uint8_t>(_input_old, top_left_window_corner_old.x() + kx, top_left_window_corner_old.y() + ky,
+ iw00_old, iw01_old, iw10_old, iw11_old, W_BITS - 5);
+ const int32_t jval = get_pixel<uint8_t>(_input_new, top_left_window_corner_new.x() + kx, top_left_window_corner_new.y() + ky,
+ iw00_new, iw01_new, iw10_new, iw11_new, W_BITS - 5);
+
+ const int32_t diff = jval - ival;
+
+ ib1 += diff * bilinear_ix[kx + ky * _window_dimension];
+ ib2 += diff * bilinear_iy[kx + ky * _window_dimension];
+ }
+ }
+
+ ib1 += vgetq_lane_s32(nb1, 0) + vgetq_lane_s32(nb1, 1) + vgetq_lane_s32(nb1, 2) + vgetq_lane_s32(nb1, 3);
+ ib2 += vgetq_lane_s32(nb2, 0) + vgetq_lane_s32(nb2, 1) + vgetq_lane_s32(nb2, 2) + vgetq_lane_s32(nb2, 3);
+
+ return std::make_pair(ib1, ib2);
+}
+
+NELKTrackerKernel::NELKTrackerKernel()
+ : _input_old(nullptr), _input_new(nullptr), _old_scharr_gx(nullptr), _old_scharr_gy(nullptr), _new_points(nullptr), _new_points_estimates(nullptr), _old_points(nullptr), _old_points_internal(),
+ _new_points_internal(), _termination(Termination::TERM_CRITERIA_EPSILON), _use_initial_estimate(false), _pyramid_scale(0.0f), _epsilon(0.0f), _num_iterations(0), _window_dimension(0), _level(0),
+ _num_levels(0), _valid_region()
+{
+}
+
+BorderSize NELKTrackerKernel::border_size() const
+{
+ return BorderSize(1);
+}
+
+void NELKTrackerKernel::configure(const ITensor *input_old, const ITensor *input_new, const ITensor *old_scharr_gx, const ITensor *old_scharr_gy,
+ const IKeyPointArray *old_points, const IKeyPointArray *new_points_estimates, IKeyPointArray *new_points,
+ INELKInternalKeypointArray *old_points_internal, INELKInternalKeypointArray *new_points_internal,
+ Termination termination, bool use_initial_estimate, float epsilon, unsigned int num_iterations, size_t window_dimension,
+ size_t level, size_t num_levels, float pyramid_scale)
+
+{
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input_old, 1, DataType::U8);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input_new, 1, DataType::U8);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(old_scharr_gx, 1, DataType::S16);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(old_scharr_gy, 1, DataType::S16);
+
+ _input_old = input_old;
+ _input_new = input_new;
+ _old_scharr_gx = old_scharr_gx;
+ _old_scharr_gy = old_scharr_gy;
+ _old_points = old_points;
+ _new_points_estimates = new_points_estimates;
+ _new_points = new_points;
+ _old_points_internal = old_points_internal;
+ _new_points_internal = new_points_internal;
+ _termination = termination;
+ _use_initial_estimate = use_initial_estimate;
+ _epsilon = epsilon;
+ _num_iterations = num_iterations;
+ _window_dimension = window_dimension;
+ _level = level;
+ _num_levels = num_levels;
+ _pyramid_scale = pyramid_scale;
+ _num_levels = num_levels;
+
+ Window window;
+ window.set(Window::DimX, Window::Dimension(0, old_points->num_values()));
+ window.set(Window::DimY, Window::Dimension(0, 1));
+
+ _valid_region = intersect_valid_regions(
+ input_old->info()->valid_region(),
+ input_new->info()->valid_region(),
+ old_scharr_gx->info()->valid_region(),
+ old_scharr_gy->info()->valid_region());
+
+ update_window_and_padding(window,
+ AccessWindowStatic(input_old->info(), _valid_region.start(0), _valid_region.start(1),
+ _valid_region.end(0), _valid_region.end(1)),
+ AccessWindowStatic(input_new->info(), _valid_region.start(0), _valid_region.start(1),
+ _valid_region.end(0), _valid_region.end(1)),
+ AccessWindowStatic(old_scharr_gx->info(), _valid_region.start(0), _valid_region.start(1),
+ _valid_region.end(0), _valid_region.end(1)),
+ AccessWindowStatic(old_scharr_gy->info(), _valid_region.start(0), _valid_region.start(1),
+ _valid_region.end(0), _valid_region.end(1)));
+
+ INEKernel::configure(window);
+}
+
+void NELKTrackerKernel::run(const Window &window)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
+
+ ARM_COMPUTE_ERROR_ON(_input_old->buffer() == nullptr);
+ ARM_COMPUTE_ERROR_ON(_input_new->buffer() == nullptr);
+ ARM_COMPUTE_ERROR_ON(_old_scharr_gx->buffer() == nullptr);
+ ARM_COMPUTE_ERROR_ON(_old_scharr_gy->buffer() == nullptr);
+
+ const int list_end = window.x().end();
+ const int list_start = window.x().start();
+
+ init_keypoints(list_start, list_end);
+
+ const int buffer_size = _window_dimension * _window_dimension;
+ int bilinear_ix[buffer_size];
+ int bilinear_iy[buffer_size];
+
+ const int half_window = _window_dimension / 2;
+
+ auto is_invalid_keypoint = [&](const NELKInternalKeypoint & keypoint)
+ {
+ const int x = std::floor(keypoint.x);
+ const int y = std::floor(keypoint.y);
+
+ return (x - half_window < _valid_region.start(0)) || (x + half_window >= _valid_region.end(0) - 1) || (y - half_window < _valid_region.start(1)) || (y + half_window >= _valid_region.end(1) - 1);
+ };
+
+ for(int list_indx = list_start; list_indx < list_end; ++list_indx)
+ {
+ NELKInternalKeypoint &old_keypoint = _old_points_internal->at(list_indx);
+ NELKInternalKeypoint &new_keypoint = _new_points_internal->at(list_indx);
+
+ if(!old_keypoint.tracking_status)
+ {
+ continue;
+ }
+
+ if(is_invalid_keypoint(old_keypoint))
+ {
+ if(_level == 0)
+ {
+ new_keypoint.tracking_status = false;
+ }
+
+ continue;
+ }
+
+ // Compute spatial gradient matrix
+ int iA11 = 0;
+ int iA12 = 0;
+ int iA22 = 0;
+
+ std::tie(iA11, iA12, iA22) = compute_spatial_gradient_matrix(old_keypoint, bilinear_ix, bilinear_iy);
+
+ const float A11 = iA11 * FLT_SCALE;
+ const float A12 = iA12 * FLT_SCALE;
+ const float A22 = iA22 * FLT_SCALE;
+
+ // Calculate minimum eigenvalue
+ const float sum_A11_A22 = A11 + A22;
+ const float discriminant = sum_A11_A22 * sum_A11_A22 - 4.0f * (A11 * A22 - A12 * A12);
+ // Divide by _window_dimension^2 to reduce the floating point accummulation error
+ const float minimum_eigenvalue = (sum_A11_A22 - std::sqrt(discriminant)) / (2.0f * _window_dimension * _window_dimension);
+
+ // Determinant
+ const double D = A11 * A22 - A12 * A12;
+
+ // Check if it is a good point to track
+ if(minimum_eigenvalue < EIGENVALUE_THRESHOLD || D < DETERMINANT_THRESHOLD)
+ {
+ // Invalidate tracked point
+ if(_level == 0)
+ {
+ new_keypoint.tracking_status = false;
+ }
+
+ continue;
+ }
+
+ float prev_delta_x = 0.0f;
+ float prev_delta_y = 0.0f;
+
+ for(unsigned int j = 0; j < _num_iterations || _termination == Termination::TERM_CRITERIA_EPSILON; ++j)
+ {
+ if(is_invalid_keypoint(new_keypoint))
+ {
+ if(_level == 0)
+ {
+ new_keypoint.tracking_status = false;
+ }
+
+ break;
+ }
+
+ // Compute image mismatch vector
+ int ib1 = 0;
+ int ib2 = 0;
+
+ std::tie(ib1, ib2) = compute_image_mismatch_vector(old_keypoint, new_keypoint, bilinear_ix, bilinear_iy);
+
+ double b1 = ib1 * FLT_SCALE;
+ double b2 = ib2 * FLT_SCALE;
+
+ // Compute motion vector -> A^-1 * -b
+ const float delta_x = (A12 * b2 - A22 * b1) / D;
+ const float delta_y = (A12 * b1 - A11 * b2) / D;
+
+ // Update the new position
+ new_keypoint.x += delta_x;
+ new_keypoint.y += delta_y;
+
+ const float mag2 = delta_x * delta_x + delta_y * delta_y;
+
+ // Check if termination criteria is EPSILON and if it is satisfied
+ if(mag2 <= _epsilon && (_termination == Termination::TERM_CRITERIA_EPSILON || _termination == Termination::TERM_CRITERIA_BOTH))
+ {
+ break;
+ }
+
+ // Check convergence analyzing the previous delta
+ if(j > 0 && std::fabs(delta_x + prev_delta_x) < 0.01f && std::fabs(delta_y + prev_delta_y) < 0.01f)
+ {
+ new_keypoint.x -= delta_x * _pyramid_scale;
+ new_keypoint.y -= delta_y * _pyramid_scale;
+ break;
+ }
+
+ prev_delta_x = delta_x;
+ prev_delta_y = delta_y;
+ }
+ }
+
+ if(_level == 0)
+ {
+ for(int list_indx = list_start; list_indx < list_end; ++list_indx)
+ {
+ const NELKInternalKeypoint &new_keypoint = _new_points_internal->at(list_indx);
+
+ _new_points->at(list_indx).x = roundf(new_keypoint.x);
+ _new_points->at(list_indx).y = roundf(new_keypoint.y);
+ _new_points->at(list_indx).tracking_status = new_keypoint.tracking_status ? 1 : 0;
+ }
+ }
+}