Reuse textures between flow invocations.

[nageru] / motion_search.frag

diff --git a/motion_search.frag b/motion_search.frag
index a417834ff3fc72c5121fb144c3a373df6d71da3b..163db2cbaf4be29dc74d749e07ce4037dda9b9f6 100644 (file)
--- a/motion_search.frag
+++ b/motion_search.frag
@@ -40,16 +40,16 @@ const uint num_iterations = 16;
 
 in vec2 flow_tc;
 in vec2 patch_bottom_left_texel;  // Center of bottom-left texel of patch.
-out vec2 out_flow;
+out vec3 out_flow;
 
 uniform sampler2D flow_tex, grad0_tex, image0_tex, image1_tex;
-uniform vec2 image_size, inv_image_size;
+uniform vec2 image_size, inv_image_size, inv_prev_level_size;
 
 void main()
 {
        // Lock patch_bottom_left_texel to an integer, so that we never get
        // any bilinear artifacts for the gradient.
-       vec2 base = round(patch_bottom_left_texel * image_size)
+       vec2 base = (round(patch_bottom_left_texel * image_size - vec2(0.5, 0.5)) + vec2(0.5, 0.5))
                * inv_image_size;
 
        // First, precompute the pseudo-Hessian for the template patch.
@@ -90,21 +90,14 @@ void main()
 
        mat2 H_inv = inverse(H);
 
-       // Fetch the initial guess for the flow. (We need the normalization step
-       // because densification works by accumulating; see the comments on the
-       // Densify class.)
-       vec3 prev_flow = texture(flow_tex, flow_tc).xyz;
-       vec2 initial_u;
-       if (prev_flow.z < 1e-3) {
-               initial_u = vec2(0.0, 0.0);
-       } else {
-               initial_u = prev_flow.xy / prev_flow.z;
-       }
+       // Fetch the initial guess for the flow.
+       vec2 initial_u = texture(flow_tex, flow_tc).xy * inv_prev_level_size;
 
        // Note: The flow is in OpenGL coordinates [0..1], but the calculations
        // generally come out in pixels since the gradient is in pixels,
        // so we need to convert at the end.
        vec2 u = initial_u;
+       float mean_diff, first_mean_diff;
 
        for (uint i = 0; i < num_iterations; ++i) {
                vec2 du = vec2(0.0, 0.0);
@@ -131,16 +124,30 @@ void main()
                //   sum(S^T * (x - y)) = [what we calculated] - (µ1 - µ2) sum(S^T)
                //
                // so we can just subtract away the mean difference here.
-               du -= grad_sum * (warped_sum - template_sum) * (1.0 / (patch_size * patch_size));
+               mean_diff = (warped_sum - template_sum) * (1.0 / (patch_size * patch_size));
+               du -= grad_sum * mean_diff;
+
+               if (i == 0) {
+                       first_mean_diff = mean_diff;
+               }
 
                // Do the actual update.
                u -= (H_inv * du) * inv_image_size;
        }
 
-       // Reject if we moved too far.
-       if (length((u - initial_u) * image_size) > patch_size) {
+       // Reject if we moved too far. Also reject if the patch goes out-of-bounds
+       // (the paper does not mention this, but the code does, and it seems to be
+       // critical to avoid really bad behavior at the edges).
+       if ((length((u - initial_u) * image_size) > patch_size) ||
+            u.x * image_size.x < -(patch_size * 0.5f) ||
+            (1.0 - u.x) * image_size.x < -(patch_size * 0.5f) ||
+            u.y * image_size.y < -(patch_size * 0.5f) ||
+            (1.0 - u.y) * image_size.y < -(patch_size * 0.5f)) {
                u = initial_u;
+               mean_diff = first_mean_diff;
        }
 
-       out_flow = u;
+       // NOTE: The mean patch diff will be for the second-to-last patch,
+       // not the true position of du. But hopefully, it will be very close.
+       out_flow = vec3(u.x, u.y, mean_diff);
 }