orbs photography
193097350
Orbs, Blobs, and Glows: Astronauts, UFOs, and Photography
Neil Armstrong saw UFOs: two pale orbs haloed in a cobalt glow hovering in a pitch black void. Or so countless websites report in copy and paste narratives replete with audio, tiny fuzzy color images, and corroborations by ex NASA employees, doctors, and even one of Neil's friends. In photographs of UFOs taken by astronauts, two divergent worlds come into the same orbit: science and the paranormal. Astronomers and ufologists both gaze into outer space, but with very different desires. The claim that our national hero Armstrong saw a UFO is either the most alluring evidence of alien intelligence out there or the most absurd. Other pixelated images purportedly taken by Armstrong show a ball of light over a spaceship on the lunar surface and a seahorse shaped blob high above earth. There they are: July 1969, alone on a cold gray ball 238,000 miles from our planet, out of range of any cameras except the ones they hold, highly trained and imbued with impeccable authority, and invested with all the dreams and aspirations of an entire nation.
Jane D Marsching
21792932
FUJIFILM X10 white orbs and DeOrbIt
The FUJIFILM X10 is a high end enthusiast compact digital camera using an unusual sensor design. Unfortunately, upon its Fall 2011 release, the camera quickly became infamous for the uniquely disturbing "white orbs" that often appeared in areas where the sensor was saturated. FUJIFILM's first attempt at a fix was firmware released on February 25, 2012 if it had little effect. In April 2012, a sensor replacement essentially solved the problem. This paper explores the "white orb" phenomenon in detail. After FUJIFILM's attempt at a firmware fix failed, the author decided to create a post processing tool that automatically could repair existing images. DeOrbIt was released as a free tool on March 7, 2012. To better understand the problem and how to fix it, the WWW form version of the tool logs images, processing parameters, and evaluations by users. The current paper describes the technical problem, the novel computational photography methods used by DeOrbit to repair affected images, and the public perceptions revealed by this experiment.
Electronic Imaging
Henry G Dietz
16866155
FUJIFILM X 10 white orbs and
The FUJIFILM X10 is a high end enthusiast compact digital camera using an unusual sensor design. Unfortunately, upon its Fall 2011 release, the camera quickly became infamous for the uniquely disturbing "white orbs" that often appeared in areas where the sensor was saturated. FUJIFILM's rst attempt at a x was rmware released on February 25, 2012 it had little e ect. In April 2012, a sensor replacement essentially solved the problem. This paper explores the "white orb" phenomenon in detail. After FUJIFILM's attempt at a rmware x failed, the author decided to create a post processing tool that automatically could repair existing images. DeOrbIt was released as a free tool on March 7, 2012. To better understand the problem and how to x it, the WWW form version of the tool logs images, processing parameters, and evaluations by users. The current paper describes the technical problem, the novel computational photography methods used by DeOrbit to repair a ected images, and the public perceptions revealed by this experiment. Figure 1. FUJIFILM X10, a White Orb, and repair implemented by DeOrbIt
Henry G Dietz
191462590
Photography and the industrial city: Manchester and Salford, ancient and modern
Abstract The photograph of 'The River Irwell from Blackfriars Bridge' (figure 1) seems emblematic over and above what it might represent. It appears to be solidly, even reassuringly balanced as if there is nothing arbitrary about the scene, and the lack of near movement helps the sense of gravity and quietness. The city appears to look back at us as an epitome of itself. When the photographer James Mudd chose this view, midway across a river and looking along the river so that it fills the foreground towards a bridge, he made the scene appear as if it were arranged around an imagined equivalence between two points: the point from which the picture is taken, and another point somewhere on that far bridge. Yet there, where that other point should be are the stone orbs that mark the mid point of the bridge's parapets, a mirror image reminding us of the parapet beside which our own lens must be located. It is as if a vanishing point, denied by the sudden bend of the river leftwards just beyond the bridge, has been bracketed for future reference. Below this mid point is a flattened oval created by the arch of the bridge and its reflection in the stilled water. That oval is like a frame or lens in which can be imagined a summary of the image as a whole: darker and more solid geometries on the left giving way to diffuse reflections and misty forms that fill the rest of the oval. (It even has its own cross hairs in the waterline crossing the vertical drain shadow. Beneath our equivalent position on the far bridge, then, there is a metaphoric mirroring of the camera eye that has opened onto the scene before us.
Mark Crinson
214006351
Guided Autonomy for Quadcopter Photography
Photographing small objects with a quadcopter is non trivial to perform with many common user interfaces, especially when it requires maneuvering an Unmanned Aerial Vehicle (UAV) to difficult angles in order to shoot high perspectives. The aim of this research is to employ machine learning to support better user interfaces for quadcopter photography. Human Robot Interaction (HRI) is supported by visual servoing, a specialized vision system for real time object detection, and control policies acquired through reinforcement learning (RL) Two investigations of guided autonomy were conducted. In the first, the user directed the quadcopter with a sketch based interface, and periods of user direction were interspersed with periods of autonomous flight. In the second, the user directs the quadcopter by taking a single photo with a handheld mobile device, and the quadcopter autonomously flies to the requested vantage point. This dissertation focuses on the following problems: 1) evaluating different user interface paradigms for dynamic photography in a GPS denied environment; 2) learning better Convolutional Neural Network (CNN) object detection models to assure a higher precision in detecting human subjects than the currently available state of the art fast models; 3) transferring learning from the Gazebo simulation into the real world; 4) learning robust control policies using deep reinforcement learning to maneuver the quadcopter to multiple shooting positions with minimal human interaction.
Saif Alabachi
204971526
Research on Fault Identification of Ship PV System Based on Aerial Photography Image Recognition
Due to the long term exposure of marine PV systems to harsh marine environments, they are exposed to wind and sun, and are susceptible to corrosion, resulting in extremely high failure rates. The existing ship PV system operation and maintenance methods are difficult to meet the wide range of fault identification. accuracy and real time requirements. With the rapid development of image recognition technology, this technology is widely used in many aspects, and is gradually being invested in the inspection of photovoltaic systems. The low cost, light and flexible UAV, combined with image recognition technology, can accurately and efficiently realize the fault identification of ship PV system. In order to solve the problem of difficult operation and maintenance of photovoltaic system, an aerial image recognition fault identification system for marine photovoltaic system was designed. The image recognition technology was used to realize the independent detection and the optimal process was selected. The effectiveness of the method was verified by experiments.
2019 5th International Conference on Transportation Information and Safety (ICTIS)
Ziyan Ma Yong-Rui Zhang Huiyuan Li
3670278
Autonomous aerial navigation using monocular visual inertial fusion
Autonomous micro aerial vehicles (MAVs) have cost and mobility benefits, making them ideal robotic platforms for applications including aerial photography, surveillance, and search and rescue. As the platform scales down, MAVs become more capable of operating in confined environments, but it also introduces significant size and payload constraints. A monocular visual inertial navigation system (VINS) consisting only of an inertial measurement unit (IMU) and a camera, becomes the most suitable sensor suite in this case, thanks to its light weight and small footprint. In fact, it is the minimum sensor suite allowing autonomous flight with sufficient environmental awareness. In this paper, we show that it is possible to achieve reliable online autonomous navigation using monocular VINS. Our system is built on a customized quadrotor testbed equipped with a fisheye camera, a low cost IMU, and heterogeneous onboard computing resources. The backbone of our system is a highly accurate optimization based monocular visual inertial state estimator with online initialization and self extrinsic calibration. An onboard GPU based monocular dense mapping module that conditions on the estimated pose provides wide angle situational awareness. Finally, an online trajectory planner that operates directly on the incrementally built three dimensional map guarantees safe navigation through cluttered environments. Extensive experimental results are provided to validate individual system modules as well as the overall performance in both indoor and outdoor environments.
J. Field Robotics
Yi Lin Fei Gao Tong Qin Wenliang Gao Tianbo Liu William Wu Zhenfei Yang Shaojie Shen
204788944
Eye in the Sky: Drone Based Object Tracking and 3D Localization
Drones, or general UAVs, equipped with a single camera have been widely deployed to a broad range of applications, such as aerial photography, fast goods delivery and most importantly, surveillance. Despite the great progress achieved in computer vision algorithms, these algorithms are not usually optimized for dealing with images or video sequences acquired by drones, due to various challenges such as occlusion, fast camera motion and pose variation. In this paper, a drone based multi object tracking and 3D localization scheme is proposed based on the deep learning based object detection. We first combine a multi object tracking method called TrackletNet Tracker (TNT) which utilizes temporal and appearance information to track detected objects located on the ground for UAV applications. Then, we are also able to localize the tracked ground objects based on the group plane estimated from the Multi View Stereo technique. The system deployed on the drone can not only detect and track the objects in a scene, but can also localize their 3D coordinates in meters with respect to the drone camera. The experiments have proved our tracker can reliably handle most of the detected objects captured by drones and achieve favorable 3D localization performance when compared with the state of the art methods.
ACM Multimedia
Hao-Tian Zhang Gaoang Wang Zhichao Lei Jenq-Neng Hwang
211105057
The Landscape in Digital Media Art: A Selection of Artworks
The landscape genre in art goes beyond the dominant landscape painting made until the 20th century. Although, during the industrial revolution, the landscape was being explored in the context of photography, cinema, and other media, it is not so clear what happened with the advent of digital media art. In this chapter the authors bring a brief context around the topic of landscape and present ten digital media art installations that constitutes an example of how, today, the landscape is being approached and explored and where the digital media assumes itself as a tool and product in the construction and production of the artistic work. The analysis is made from the visual culture and social semiotics point of view in order to expose how the landscape concept evolve and how is it being used in the field of digital media art.
ARTECH
Tiago Cruz Fernando Faria Paulino Mirian Nogueira Tavares
209466758
STEREO VISION APPLYING OPENCV AND RASPBERRY PI
Abstract. This article points out the single board computer Raspberry Pi and the related camera modules for image acquisition. Particular attention is directed to stereoscopic image recording and post processing software applying OpenCV. A design of a camera network is created and applied to a field application. The OpenCV computer vision library and its Python binding provides some script samples to encourage users developing their own custom tailored scripts. Stereoscopic recording is intended for extended base lines without a mechanical bar. Image series will be taken in order to wipe out moving objects from the frames. And finally the NoIR camera made infrared photography possible with low effort. Computer, accupack and lens board are assembled in a 3D printed housing operated by a mobile device.
Gunter Pomaska