構造化ハフ投票による視覚ベースの高速道路境界検出
Structured Hough Voting for Vision-based Highway Border Detection
道路境界と車線標示の幾何学的関係を利用し、検出と追跡を統合した構造化ハフ投票で高速道路の境界を頑健に検出する手法を提案した論文。
著者: Zhiding Yu, Wende Zhang, B. V. K. Vijaya Kumar, Dan Levi
分類: cs.CV, cs.RO
原文アブストラクト
We propose a vision-based highway border detection algorithm using structured Hough voting. Our approach takes advantage of the geometric relationship between highway road borders and highway lane markings. It uses a strategy where a number of trained road border and lane marking detectors are triggered, followed by Hough voting to generate corresponding detection of the border and lane marking. Since the initially triggered detectors usually result in large number of positives, conventional frame-wise Hough voting is not able to always generate robust border and lane marking results. Therefore, we formulate this problem as a joint detection-and-tracking problem under the structured Hough voting model, where tracking refers to exploiting inter-frame structural information to stabilize the detection results. Both qualitative and quantitative evaluations show the superiority of the proposed structured Hough voting model over a number of baseline methods.
