Motion blur plays a critical role in enhancing the realism and dynamism of rendered imagery by simulating the perception of motion captured in real-world cameras. Traditional methods, such as accumulation buffering and texture-based blurring, provide convincing results but often suffer from performance inefficiencies or limited flexibility. McGuire's algorithm introduced a velocity-based approach that improves the quality and stability of motion blur through the use of velocity, tile, and neighborhood velocity maps. However, it can produce visible artifacts in cases of overlapping high-velocity objects. This paper presents \textit{Guertin’s Motion Blur}, an enhanced algorithm that mitigates these artifacts while maintaining performance and visual fidelity. By refining sample weighting and incorporating perpendicular sampling directions relative to tile velocities, Guertin’s method achieves smoother transitions and reduces hallucinated blur effects. The proposed approach provides a fast, stable, and visually accurate solution suitable for both real-time rendering and still image generation, with additional potential for integration into ray-traced and stylized rendering pipelines.