Probabilistic Estimation of Area- and Feature-based Stereo Matching Results Considering Uncertatinty

불확실성을 고려한 영역과 특징기반 스테레오 정합결과의 확률적 통합

This paper proposes a positional estimation method for extracted line features by stereo vision. Based on given reference plane, planar surfaces corresponding the given plane are first extracted. Then, features in the planar surfaces are selected. Using the Extended Kalman Filter the feature positions are estimated by combining area- and feature-based stereo matching results. Experimental results show the proposed method is feasible.