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—We present a new parametrization for point features within monocular simultaneous localization and mapping (SLAM) that permits efficient and accurate representation of uncertainty during undelayed initialization and beyond, all within the standard extended Kalman filter (EKF). The key concept is direct parametrization of the inverse depth of features(More)
Object detectors are typically trained on a large set of still images annotated by bounding-boxes. This paper introduces an approach for learning object detectors from real-world web videos known only to contain objects of a target class. We propose a fully automatic pipeline that localizes objects in a set of videos of the class and learns a detector for(More)
— Recent work has shown that the probabilistic SLAM approach of explicit uncertainty propagation can succeed in permitting repeatable 3D real-time localization and mapping even in the 'pure vision' domain of a single agile camera with no extra sensing. An issue which has caused difficulty in monocular SLAM however is the initialization of features, since(More)
— Recently, classical pairwise Structure From Motion (SfM) techniques have been combined with non-linear global optimization (Bundle Adjustment, BA) over a sliding window to recursively provide camera pose and feature location estimation from long image sequences. Normally called Visual Odometry, these algorithms are nowadays able to estimate with(More)
This paper explores the impact that landmark parametrization has in the performance of monocular, EKF-based, 6-DOF simultaneous localization and mapping (SLAM) in the context of undelayed landmark initialization. Undelayed initialization in monocular SLAM challenges EKF because of the combination of non-linearity with the large uncertainty associated with(More)
— In recent years, research on visual SLAM has produced robust algorithms providing, in real time at 30 Hz, both the 3D model of the observed rigid scene and the 3D camera motion using as only input the gathered image sequence. These algorithms have been extensively validated in rigid human-made environments –indoor and outdoor– showing robust performance(More)
— Recently it has been shown that an inverse depth parametrization can improve the performance of real-time monocular EKF SLAM, permitting undelayed initialization of features at all depths. However, the inverse depth parametriza-tion requires the storage of 6 parameters in the state vector for each map point. This implies a noticeable computing overhead(More)