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

Mixed marker-based/marker-less visual odometry system for mobile robots

When moving in generic indoor environments, robotic platforms generally rely solely on information provided by onboard sensors to determine their position and orientation. However, the lack of absolute references often leads to the introduction of severe drifts in estimates computed, making autonomous operations really hard to accomplish. This paper proposes a solution to alleviate the impact of the above issues by combining two vision‐based pose estimation techniques working on relative and absolute coordinate systems, respectively. In particular, the unknown ground features in the images that are captured by the vertical camera of a mobile platform are processed by a vision‐based odometry algorithm, which is capable of estimating the relative frame‐to‐frame movements. Then, errors accumulated in the above step are corrected using artificial markers displaced at known positions in the environment. The markers are framed from time to time, which allows the robot to maintain the drifts bounded by additionally providing it with the navigation commands needed for autonomous flight. Accuracy and robustness of the designed technique are demonstrated using an off‐the‐shelf quadrotor via extensive experimental test

Viewing the Future? Virtual Reality In Journalism

Journalism underwent a flurry of virtual reality content creation, production and distribution starting in the final months of 2015. The New York Times distributed more than 1 million cardboard virtual reality viewers and released an app showing a spherical video short about displaced refugees. The Los Angeles Times landed people next to a crater on Mars. USA TODAY took visitors on a ride-along in the "Back to the Future" car on the Universal Studios lot and on a spin through Old Havana in a bright pink '57 Ford. ABC News went to North Korea for a spherical view of a military parade and to Syria to see artifacts threatened by war. The Emblematic Group, a company that creates virtual reality content, followed a woman navigating a gauntlet of anti- abortion demonstrators at a family planning clinic and allowed people to witness a murder-suicide stemming from domestic violence.In short, the period from October 2015 through February 2016 was one of significant experimentation with virtual reality (VR) storytelling. These efforts are part of an initial foray into determining whether VR is a feasible way to present news. The year 2016 is shaping up as a period of further testing and careful monitoring of potential growth in the use of virtual reality among consumers