46,766 research outputs found
RGB-D datasets using microsoft kinect or similar sensors: a survey
RGB-D data has turned out to be a very useful representation of an indoor scene for solving fundamental computer vision problems. It takes the advantages of the color image that provides appearance information of an object and also the depth image that is immune to the variations in color, illumination, rotation angle and scale. With the invention of the low-cost Microsoft Kinect sensor, which was initially used for gaming and later became a popular device for computer vision, high quality RGB-D data can be acquired easily. In recent years, more and more RGB-D image/video datasets dedicated to various applications have become available, which are of great importance to benchmark the state-of-the-art. In this paper, we systematically survey popular RGB-D datasets for different applications including object recognition, scene classification, hand gesture recognition, 3D-simultaneous localization and mapping, and pose estimation. We provide the insights into the characteristics of each important dataset, and compare the popularity and the difficulty of those datasets. Overall, the main goal of this survey is to give a comprehensive description about the available RGB-D datasets and thus to guide researchers in the selection of suitable datasets for evaluating their algorithms
Markerless visual servoing on unknown objects for humanoid robot platforms
To precisely reach for an object with a humanoid robot, it is of central
importance to have good knowledge of both end-effector, object pose and shape.
In this work we propose a framework for markerless visual servoing on unknown
objects, which is divided in four main parts: I) a least-squares minimization
problem is formulated to find the volume of the object graspable by the robot's
hand using its stereo vision; II) a recursive Bayesian filtering technique,
based on Sequential Monte Carlo (SMC) filtering, estimates the 6D pose
(position and orientation) of the robot's end-effector without the use of
markers; III) a nonlinear constrained optimization problem is formulated to
compute the desired graspable pose about the object; IV) an image-based visual
servo control commands the robot's end-effector toward the desired pose. We
demonstrate effectiveness and robustness of our approach with extensive
experiments on the iCub humanoid robot platform, achieving real-time
computation, smooth trajectories and sub-pixel precisions
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