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Event-based cameras provide a new visual sensing model by detecting changes in image intensity asynchronously across all pixels on the camera. By providing these events at extremely high rates (up to 1MHz), they allow for sensing in both high speed and high dynamic range situations where traditional cameras may fail. In this paper, we present the first algorithm to fuse a purely event-based tracking...
Asynchronous event-based sensors present new challenges in basic robot vision problems like feature tracking. The few existing approaches rely on grouping events into models and computing optical flow after assigning future events to those models. Such a hard commitment in data association attenuates the optical flow quality and causes shorter flow tracks. In this paper, we introduce a novel soft...
We present PennCOSYVIO, a new challenging Visual Inertial Odometry (VIO) benchmark with synchronized data from a VI-sensor (stereo camera and IMU), two Project Tango hand-held devices, and three GoPro Hero 4 cameras. Recorded at UPenn's Singh center, the 150m long path of the hand-held rig crosses from outdoors to indoors and includes rapid rotations, thereby testing the abilities of VIO and Simultaneous...
This paper presents a novel approach to estimating the continuous six degree of freedom (6-DoF) pose (3D translation and rotation) of an object from a single RGB image. The approach combines semantic keypoints predicted by a convolutional network (convnet) with a deformable shape model. Unlike prior work, we are agnostic to whether the object is textured or textureless, as the convnet learns the optimal...
We present a system for determining a global solution for the relative poses between multiple sensors with different modalities and varying fields of view. The final calibration result produces a tree of transforms rooted at a single sensor that allows the fusion of the sensor streams into a shared coordinate frame. The method differs from other approaches by handling any number of sensors with only...
The development of fully autonomous seafaring vessels has enormous implications to the world's global supply chain and militaries. To obey international marine traffic regulations, these vessels must be equipped with machine vision systems that can classify other ships nearby during the day and night. In this paper, we address this problem by introducing VAIS, the world's first publicly available...
This paper presents an online self-supervised approach to monocular visual odometry and ground classification applied to ground vehicles. We solve the motion and structure problem based on a constrained kinematic model. The true scale of the monocular scene is recovered by estimating the ground surface. We consider a general parametric ground surface model and use the Random Sample Consensus (RANSAC)...
In many scenarios, robots encounter rotationally symmetric objects for which no known 3D model exists. To be able to grasp such objects using existing grasp point computation schemes, an estimate of their 3D-pose and shape is necessary. In this paper, we address the problem of recovering 3D-pose and shape of an unknown surface of revolution from two perspective views of known relative orientation...
The ego motion estimation from an image sequence, commonly known as visual odometry, has been thoroughly studied in recent years. Different solutions have been developed depending on the particular scenario the system interacts in. In highly textured environments point features are abundant and visual odometry approaches focus on complementary steps, such as sparse bundle adjustment or keyframe techniques,...
We formulate the position-based visual servoing problem for a quadrotor equipped with a monocular camera and an IMU relying only on features on planes and lines in order to fly above and perch on arbitrarily oriented lines. We show that we are able to compute the orientation of an arbitrarily oriented line, the speed of the robot and its position with respect to the target line using two points at...
We present an approach for sensor network localization when provided with a set of angular constraints. This problem arises in camera networks when angles between nearby points can be measured but depth measurements are not readily available. We provide contributions for two different variations on this problem. First, when each node is aware of a global coordinate frame, we present a novel method...
In this paper, we give a new double twist to the robot localization problem. We solve the problem for the case of prior maps which are semantically annotated perhaps even sketched by hand. Data association is achieved not through the detection of visual features but the detection of object classes used in the annotation of the prior maps. To avoid the caveats of general object recognition, we propose...
The visual perception of semi-transparent objects, such as drinking glasses, is an open challenging problem. Unlike opaque objects, semi-transparent objects violate many of the standard vision assumptions, among them that figure-ground segmentation contains salient boundaries. More specifically, reliable motion and stereo cues for segmenting semi-transparent objects are not present because of the...
This paper presents a new method to estimate the relative motion of a vehicle from images of a single camera. The biggest problem in visual motion estimation is data association; matched points contain many outliers that must be detected and removed so that the motion can be estimated accurately. A very established method for robust motion estimation in the presence of outliers is the five-point RANSAC...
We propose a new method for extrinsic calibration of a line-scan LIDAR with a perspective projection camera. Our method is a closed-form, minimal solution to the problem. The solution is a symbolic template found via variable elimination and the multi-polynomial Macaulay resultant. It does not require initialization, and can be used in an automatic calibration setting when paired with RANSAC and least-squares...
In this paper, we present a system for indoor human localization that does not need 3D reconstruction of features or landmarks. We assume that a video sequence has been acquired and that keyframes have been registered with respect to 2D positions and orientations. In online mode, we use only a handheld monochrome fisheye camera and a synchronized IMU as sensory inputs. The query is not based on a...
A pair of stereo images are said to be rectified if corresponding image points have the same y-coordinate in their respective images. In this paper we consider the rectification of two omnidirectional cameras, specifically two parabolic catadioptric cameras. Such systems consist of a parabolic mirror and an orthographically projecting lens. We show that if the image coordinates are represented as...
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