The fundamental matrix is an effective tool to analyze epipolar geometry and plays an important role in computer vision. This paper analyzes the shortcoming of traditional robust methods in estimating the fundamental matrix

and proposes a novel technique for estimating the fundamental matrix using LQS and bucketing technique in robust regression

which eliminates the drawbacks of RANSAC and LMedS. Experimental results on synthetic data and real images show that the proposed algorithm achieves high accuracy and robustness.