待たせたな！(スネーク風)
(さらに…)

A Fast and Stable Feature-Aware Motion Blur Filterの疑似コード。

float cone(float dist, float r) {
	return saturate(1.0f - abs(dist) / r);
}

float cylinder(float dist, float r) {
		return sign(r - abs(dist)) * 0.5f + 0.5f;
}

// linear depth.
float zCompare(float za, float zb) {
		const float SOFT_Z_EXTENT = 0.1f;
		return saturate(1.0 - (za - ab) / SOFT_Z_EXTENT);
}

float3 MotionBlur(float2 p)
{
	// parameter setting (see. 5. Implementation and Results).
	const auto N		= 35;	// sample count.
	const auto eta		= 0.95; // a larger maximum jitter value (in pixel units). (see p.6)
	const auto phi		= 27;	// user-determined constant which affects the "baseline2 jitter level. (see p.6)
	const auto kappa	= 40;	// use-parameter to bais its importance. (see p.6)
	const auto r		= 40;	// a maximum image-space blur radius. (see p.2)
	const auto gamma	= 1.5;	// minimum user threshold (see p.4)

	auto j = Halton(-1, 1);

	// sOffset jitters a tile lookup (but never into a diagonal tile).
	auto vmax = FetchNeighborMax(p/r + sOffset(p, j));
	auto mag_vmax = length(vmax);
	if (mag_vmax <= 0.5f)
	{
		return FetchColor(p);
	}

	auto wn = vmax / mag_vmax;
	auto vc = FetchVelocity(p);
	auto wp = (-wn.y, wn.x); // vmax⊥.

	if (dot(wp, vc) < 0.0)
	{
		wp = -wp;
	}

	auto mag_vc = length(vc);
	auto wc = normalize(lerp(normalize(vc), wp, (mag_vc - 0.5) / gamma); // Eq. (1).

	// First integration samples: p with center weight
	auto totalWeight = N / (kappa * mag_vc);
	auto result = FetchColor(p) * totalWeight;
	auto j_dash = j * eta * phi / N;

	auto z_p = FetchDepth(p);

	for(int i=0; i<N; ++i)
	{
		auto t = lerp(-1.0, 1.0, (i+j_dash + 1)/(N+1)); // jitter sampler

		// Compute point S; split samples between {vmax, vc}
		auto d = (i & 0x1) ? vc : vmax; // iが奇数なら vc,　iが偶数なら vmax.
		auto T = t * mag_vmax;
		auto S = int2(t * d) + p;

		// Compute S's velocity and color
		auto vs = FetchVelocity(S);
		auto colorSmaple = FetchColor(S);

		auto z_S = FetchDepth(S);

		// Fore-vs. background classification Y w.r.t p
		auto f = zCompare(z_p, z_S);
		auto b = zCompare(z_S, z_p);

		// Sample weight and velocity-aware factors (Sec.4.1)
		// The length of v_s is clamped to 0.5 minimum during normalization
		auto weight = 0;
		auto wA = dot(wc, d);
		auto wB = dot(normalize(vs), d);

		auto mag_vs = length(vs);

		// 3 phenomenological cases (Sec. 3, 4.1): Object
		// moving over p, p's blurred motion, & their blending.
		weight += dot(f, cone(T, 1 / mag_vs)) * wB;
		weight += dot(b, cone(T, 1 / mag_vc)) * wA;
		weight += cylinder(T, min(mag_vs, mag_vc)) * max(wA, wB) * 2;

		totalWeight += weight; // For normalization
		result += colorSample * weight;
	}

	return result / totalWeight;
}

McGuireのG3Dエンジンでは論文実装よりも変更がある。以下のように内積計算部分がガッツリなくなっている。
https://sourceforge.net/p/g3d/code/HEAD/tree/G3D10/data-files/shader/MotionBlur/MotionBlur_gather.pix

auto f = zCompare(z_p, z_S);
auto b = zCompare(z_S, z_p);

auto weight = 0.0f;
weight += b * cone(T, 1 / mag_vs);
weight += f * cone(T, 1 / mag_vc);
weight += cylinder(T, min(mag_vs, mag_vc)) * 2.0f;

totalWeight += weight;
result += colorSample * weight;