Kazuhisa Ishimaru

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This paper proposes a new real-time stereo matching algorithm paired with an online auto-rectification framework. The algorithm treats disparities of stereo images as hidden states and conducts Viterbi process at 4 bi-directional paths to estimate them. Structural similarity, total variation constraint, and a specific hierarchical merging strategy are(More)
This paper proposes a novel real-time stereo matching algorithm paired with an online auto-rectification framework to solve environment sensing problems in autonomous driving, such as road, curb and small object detection etc. The algorithm treats disparities of stereo images as hidden states and conducts a Viterbi process at 4 bi-directional paths to(More)
Reconstructing the depth information from the 3D scene using stereo vision is a key element in the development of advanced driver assistance systems. We previously proposed a novel real-time stereo matching method based on the Multi-paths Viterbi that outperforms the well-known SGBM (Semi-Global Block-Matching Algorithm) algorithm in both disparity accuracy(More)
Stereo reconstruction generally requires image correspondence such as point and line correspondences in multiple images. Cameras need to be synchronized to obtain corresponding points of time-varying shapes. However, the image information obtained from synchronized multiple cameras is redundant, and has limitations with resolution. In this paper, we show(More)
Nowadays, the driverless automobiles have become a near reality and are going to become widely available. For autonomous navigation, the vehicles need to precise localize itself within a pre-defined map. In this paper, we propose a novel algorithm for the problem of three-dimensional (3D) point cloud map (PCL) based localization using a stereo camera. This(More)
In this paper, we propose a real-time vision-based filtering algorithm for steering angle estimation in autonomous driving. A novel scene-based particle filtering algorithm is used to estimate and track the steering angle using images obtained from a monocular camera. Highly accurate proposal distributions and likelihood are modeled for the second order(More)