This paper proposes a Learning Kalman Network (LKN) based monocular visual odometry (VO), i.e. LKN-VO, for on-road driving. Most existing learning-based VO focus on ego-motion estimation by comparing the two most recent consecutive frames. By contrast, the LKN-VO incorporates a learning ego-motion estimation through the current measurement, and a discriminative state estimator through a sequence of previous measurements. Superior to the model-based monocular VO, a more accurate absolute scale can be learned by LKN without any geometric constraints. In contrast to the model-based Kalman Filter (KF), the optimal model parameters of LKN can be obtained from dynamic and deterministic outputs of the neural network without elaborate human design....
Accurate camera ego-motion estimation, widely known as Visual Odometry (VO), remains a key prerequis...
We present a self-supervised approach to ignoring “distractors” in camera images for the purposes of...
publisher: Elsevier articletitle: Stereo visual odometry in urban environments based on detecting gr...
This paper proposes a Learning Kalman Network (LKN) based monocular visual odometry (VO), i.e. LKN-V...
This paper introduces a fully deep learning approach to monocular SLAM, which can perform simultaneo...
The technology of advanced driver assistance systems (ADAS) has rapidly developed in the last few de...
Visual odometry is the process of estimating incremental localization of the camera in 3-dimensional...
Autonomous vehicles require knowing their state in the environment to make a decision and achieve th...
This thesis addresses the problem of incremental localization from visual information, a scenario co...
Driver situation awareness is critical for safety. In this paper, we propose a fast, accurate method...
Precise pose information is a fundamental prerequisite for numerous applications in robotics, Artifi...
Proceedings of the International Conference on Computer Vision Theory and Applications, 361-365, 201...
While Convolutional Neural Networks (CNNs) can estimate frame-to-frame (F2F) motion even with monocu...
From the accumulation of past and repeated experiences, driving a vehicle for most people has become...
Visual odometry is a challenging approach to simultaneous localization and mapping algorithms. Based...
Accurate camera ego-motion estimation, widely known as Visual Odometry (VO), remains a key prerequis...
We present a self-supervised approach to ignoring “distractors” in camera images for the purposes of...
publisher: Elsevier articletitle: Stereo visual odometry in urban environments based on detecting gr...
This paper proposes a Learning Kalman Network (LKN) based monocular visual odometry (VO), i.e. LKN-V...
This paper introduces a fully deep learning approach to monocular SLAM, which can perform simultaneo...
The technology of advanced driver assistance systems (ADAS) has rapidly developed in the last few de...
Visual odometry is the process of estimating incremental localization of the camera in 3-dimensional...
Autonomous vehicles require knowing their state in the environment to make a decision and achieve th...
This thesis addresses the problem of incremental localization from visual information, a scenario co...
Driver situation awareness is critical for safety. In this paper, we propose a fast, accurate method...
Precise pose information is a fundamental prerequisite for numerous applications in robotics, Artifi...
Proceedings of the International Conference on Computer Vision Theory and Applications, 361-365, 201...
While Convolutional Neural Networks (CNNs) can estimate frame-to-frame (F2F) motion even with monocu...
From the accumulation of past and repeated experiences, driving a vehicle for most people has become...
Visual odometry is a challenging approach to simultaneous localization and mapping algorithms. Based...
Accurate camera ego-motion estimation, widely known as Visual Odometry (VO), remains a key prerequis...
We present a self-supervised approach to ignoring “distractors” in camera images for the purposes of...
publisher: Elsevier articletitle: Stereo visual odometry in urban environments based on detecting gr...