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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Video Compression Study: h.265 vs h.264

H.265 video compression (also known as High Efficiency Video Encoding (HEVC)) promises to provide double the video quality at half the bandwidth, or the same quality at half the bandwidth of h.264 video compression [1]. This study uses a Tektronix PQA500 to determine the video quality gains by using h.265 encoding. This study also compares two video encoders to see how different implementations of h.264 and h.265 impact video quality at various bandwidths.

Pryor, Jonathan↗
NASA NTRS1986

Analog Video Image-Enhancing Device

Inexpensive system yields pseudo-three-dimensional effect. Includes video camera with lens, connected to video monitor for analog video enhancement. Video signal obtained from monitor at point beyond where synchronization signals are detected, eliminating need to regenerate composite video signal. Analog video image-enhancing device improves appearance of technical photographs by selectively compressing overall dynamic ranges while accentuating edges or small details of greatest interest.

Weinstein, L. M.↗
NASA NTRS1990

State of the art in video system performance

The closed circuit television (CCTV) system that is onboard the Space Shuttle has the following capabilities: camera, video signal switching and routing unit (VSU); and Space Shuttle video tape recorder. However, this system is inadequate for use with many experiments that require video imaging. In order to assess the state-of-the-art in video technology and data storage systems, a survey was conducted of the High Resolution, High Frame Rate Video Technology (HHVT) products. The performance of the state-of-the-art solid state cameras and image sensors, video recording systems, data transmission devices, and data storage systems versus users' requirements are shown graphically.

Lewis, Michael J.↗
NASA NTRS1994

Advanced Video Analysis Needs for Human Performance Evaluation

Evaluators of human task performance in space missions make use of video as a primary source of data. Extraction of relevant human performance information from video is often a labor-intensive process requiring a large amount of time on the part of the evaluator. Based on the experiences of several human performance evaluators, needs were defined for advanced tools which could aid in the analysis of video data from space missions. Such tools should increase the efficiency with which useful information is retrieved from large quantities of raw video. They should also provide the evaluator with new analytical functions which are not present in currently used methods. Video analysis tools based on the needs defined by this study would also have uses in U.S. industry and education. Evaluation of human performance from video data can be a valuable technique in many industrial and institutional settings where humans are involved in operational systems and processes.

Campbell, Paul D.↗
NASA NTRS1994

A Macintosh-Based Scientific Images Video Analysis System

A set of experiments was designed at MIT's Man-Vehicle Laboratory in order to evaluate the effects of zero gravity on the human orientation system. During many of these experiments, the movements of the eyes are recorded on high quality video cassettes. The images must be analyzed off-line to calculate the position of the eyes at every moment in time. To this aim, I have implemented a simple inexpensive computerized system which measures the angle of rotation of the eye from digitized video images. The system is implemented on a desktop Macintosh computer, processes one play-back frame per second and exhibits adequate levels of accuracy and precision. The system uses LabVIEW, a digital output board, and a video input board to control a VCR, digitize video images, analyze them, and provide a user friendly interface for the various phases of the process. The system uses the Concept Vi LabVIEW library (Graftek's Image, Meudon la Foret, France) for image grabbing and displaying as well as translation to and from LabVIEW arrays. Graftek's software layer drives an Image Grabber board from Neotech (Eastleigh, United Kingdom). A Colour Adapter box from Neotech provides adequate video signal synchronization. The system also requires a LabVIEW driven digital output board (MacADIOS II from GW Instruments, Cambridge, MA) controlling a slightly modified VCR remote control used mainly to advance the video tape frame by frame.

Groleau, Nicolas↗
NASA NTRS1997

Automated Assessment of Visual Quality of Digital Video

The advent of widespread distribution of digital video creates a need for automated methods for evaluating visual quality of digital video. This is particularly so since most digital video is compressed using lossy methods, which involve the controlled introduction of potentially visible artifacts. Compounding the problem is the bursty nature of digital video, which requires adaptive bit allocation based on visual quality metrics. In previous work, we have developed visual quality metrics for evaluating, controlling, and optimizing the quality of compressed still images[1-4]. These metrics incorporate simplified models of human visual sensitivity to spatial and chromatic visual signals. The challenge of video quality metrics is to extend these simplified models to temporal signals as well. In this presentation I will discuss a number of the issues that must be resolved in the design of effective video quality metrics. Among these are spatial, temporal, and chromatic sensitivity and their interactions, visual masking, and implementation complexity. I will also touch on the question of how to evaluate the performance of these metrics.

Watson, Andrew B.↗
NASA NTRS1998

Towards a Visual Quality Metric for Digital Video

The advent of widespread distribution of digital video creates a need for automated methods for evaluating visual quality of digital video. This is particularly so since most digital video is compressed using lossy methods, which involve the controlled introduction of potentially visible artifacts. Compounding the problem is the bursty nature of digital video, which requires adaptive bit allocation based on visual quality metrics. In previous work, we have developed visual quality metrics for evaluating, controlling, and optimizing the quality of compressed still images. These metrics incorporate simplified models of human visual sensitivity to spatial and chromatic visual signals. The challenge of video quality metrics is to extend these simplified models to temporal signals as well. In this presentation I will discuss a number of the issues that must be resolved in the design of effective video quality metrics. Among these are spatial, temporal, and chromatic sensitivity and their interactions, visual masking, and implementation complexity. I will also touch on the question of how to evaluate the performance of these metrics.

Watson, Andrew B.↗
NASA NTRS2004

Video-Guidance Design for the DART Rendezvous Mission

NASA's Demonstration of Autonomous Rendezvous Technology (DART) mission will validate a number of different guidance technologies, including state-differenced GPS transfers and close-approach video guidance. The video guidance for DART will employ NASA/Marshall s Advanced Video Guidance Sensor (AVGS). This paper focuses on the terminal phase of the DART mission that includes close-approach maneuvers under AVGS guidance. The closed-loop video guidance design for DART is driven by a number of competing requirements, including a need for maximizing tracking bandwidths while coping with measurement noise and the need to minimize RCS firings. A range of different strategies for attitude control and docking guidance have been considered for the DART mission, and design decisions are driven by a goal of minimizing both the design complexity and the effects of video guidance lags. The DART design employs an indirect docking approach, in which the guidance position targets are defined using relative attitude information. Flight simulation results have proven the effectiveness of the video guidance design.

Ruth, Michael↗
NASA NTRS2004

Synchronization of video recording and laser pulses including background light suppression

An apparatus for and a method of triggering a pulsed light source, in particular a laser light source, for predictable capture of the source by video equipment. A frame synchronization signal is derived from the video signal of a camera to trigger the laser and position the resulting laser light pulse in the appropriate field of the video frame and during the opening of the electronic shutter, if such shutter is included in the camera. Positioning of the laser pulse in the proper video field allows, after recording, for the viewing of the laser light image with a video monitor using the pause mode on a standard cassette-type VCR. This invention also allows for fine positioning of the laser pulse to fall within the electronic shutter opening. For cameras with externally controllable electronic shutters, the invention provides for background light suppression by increasing shutter speed during the frame in which the laser light image is captured. This results in the laser light appearing in one frame in which the background scene is suppressed with the laser light being uneffected, while in all other frames, the shutter speed is slower, allowing for the normal recording of the background scene. This invention also allows for arbitrary (manual or external) triggering of the laser with full video synchronization and background light suppression.

Kalshoven, Jr., James E.↗
NASA NTRS2007

Video Guidance Sensor and Time-of-Flight Rangefinder

A proposed video guidance sensor (VGS) would be based mostly on the hardware and software of a prior Advanced VGS (AVGS), with some additions to enable it to function as a time-of-flight rangefinder (in contradistinction to a triangulation or image-processing rangefinder). It would typically be used at distances of the order of 2 or 3 kilometers, where a typical target would appear in a video image as a single blob, making it possible to extract the direction to the target (but not the orientation of the target or the distance to the target) from a video image of light reflected from the target. As described in several previous NASA Tech Briefs articles, an AVGS system is an optoelectronic system that provides guidance for automated docking of two vehicles. In the original application, the two vehicles are spacecraft, but the basic principles of design and operation of the system are applicable to aircraft, robots, objects maneuvered by cranes, or other objects that may be required to be aligned and brought together automatically or under remote control. In a prior AVGS system of the type upon which the now-proposed VGS is largely based, the tracked vehicle is equipped with one or more passive targets that reflect light from one or more continuous-wave laser diode(s) on the tracking vehicle, a video camera on the tracking vehicle acquires images of the targets in the reflected laser light, the video images are digitized, and the image data are processed to obtain the direction to the target. The design concept of the proposed VGS does not call for any memory or processor hardware beyond that already present in the prior AVGS, but does call for some additional hardware and some additional software. It also calls for assignment of some additional tasks to two subsystems that are parts of the prior VGS: a field-programmable gate array (FPGA) that generates timing and control signals, and a digital signal processor (DSP) that processes the digitized video images. The additional timing and control signals generated by the FPGA would cause the VGS to alternate between an imaging (direction-finding) mode and a time-of-flight (range-finding mode) and would govern operation in the range-finding mode.

Bryan, Thomas↗
NASA NTRS2011

Method and System for Temporal Filtering in Video Compression Systems

Three related innovations combine improved non-linear motion estimation, video coding, and video compression. The first system comprises a method in which side information is generated using an adaptive, non-linear motion model. This method enables extrapolating and interpolating a visual signal, including determining the first motion vector between the first pixel position in a first image to a second pixel position in a second image; determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image; determining a third motion vector between the first pixel position in the first image and the second pixel position in the second image, the second pixel position in the second image, and the third pixel position in the third image using a non-linear model; and determining a position of the fourth pixel in a fourth image based upon the third motion vector. For the video compression element, the video encoder has low computational complexity and high compression efficiency. The disclosed system comprises a video encoder and a decoder. The encoder converts the source frame into a space-frequency representation, estimates the conditional statistics of at least one vector of space-frequency coefficients with similar frequencies, and is conditioned on previously encoded data. It estimates an encoding rate based on the conditional statistics and applies a Slepian-Wolf code with the computed encoding rate. The method for decoding includes generating a side-information vector of frequency coefficients based on previously decoded source data and encoder statistics and previous reconstructions of the source frequency vector. It also performs Slepian-Wolf decoding of a source frequency vector based on the generated side-information and the Slepian-Wolf code bits. The video coding element includes receiving a first reference frame having a first pixel value at a first pixel position, a second reference frame having a second pixel value at a second pixel position, and a third reference frame having a third pixel value at a third pixel position. It determines a first motion vector between the first pixel position and the second pixel position, a second motion vector between the second pixel position and the third pixel position, and a fourth pixel value for a fourth frame based upon a linear or nonlinear combination of the first pixel value, the second pixel value, and the third pixel value. A stationary filtering process determines the estimated pixel values. The parameters of the filter may be predetermined constants.

Lu, Ligang↗
NASA NTRS2005

Video Mosaicking for Inspection of Gas Pipelines

A vision system that includes a specially designed video camera and an image-data-processing computer is under development as a prototype of robotic systems for visual inspection of the interior surfaces of pipes and especially of gas pipelines. The system is capable of providing both forward views and mosaicked radial views that can be displayed in real time or after inspection. To avoid the complexities associated with moving parts and to provide simultaneous forward and radial views, the video camera is equipped with a wide-angle (>165 ) fish-eye lens aimed along the axis of a pipe to be inspected. Nine white-light-emitting diodes (LEDs) placed just outside the field of view of the lens (see Figure 1) provide ample diffuse illumination for a high-contrast image of the interior pipe wall. The video camera contains a 2/3-in. (1.7-cm) charge-coupled-device (CCD) photodetector array and functions according to the National Television Standards Committee (NTSC) standard. The video output of the camera is sent to an off-the-shelf video capture board (frame grabber) by use of a peripheral component interconnect (PCI) interface in the computer, which is of the 400-MHz, Pentium II (or equivalent) class. Prior video-mosaicking techniques are applicable to narrow-field-of-view (low-distortion) images of evenly illuminated, relatively flat surfaces viewed along approximately perpendicular lines by cameras that do not rotate and that move approximately parallel to the viewed surfaces. One such technique for real-time creation of mosaic images of the ocean floor involves the use of visual correspondences based on area correlation, during both the acquisition of separate images of adjacent areas and the consolidation (equivalently, integration) of the separate images into a mosaic image, in order to insure that there are no gaps in the mosaic image. The data-processing technique used for mosaicking in the present system also involves area correlation, but with several notable differences: Because the wide-angle lens introduces considerable distortion, the image data must be processed to effectively unwarp the images (see Figure 2). The computer executes special software that includes an unwarping algorithm that takes explicit account of the cylindrical pipe geometry. To reduce the processing time needed for unwarping, parameters of the geometric mapping between the circular view of a fisheye lens and pipe wall are determined in advance from calibration images and compiled into an electronic lookup table. The software incorporates the assumption that the optical axis of the camera is parallel (rather than perpendicular) to the direction of motion of the camera. The software also compensates for the decrease in illumination with distance from the ring of LEDs.

Magruder, Darby↗
NASA NTRS2013

Video Altimeter and Obstruction Detector for an Aircraft

Video-based altimetric and obstruction detection systems for aircraft have been partially developed. The hardware of a system of this type includes a downward-looking video camera, a video digitizer, a Global Positioning System receiver or other means of measuring the aircraft velocity relative to the ground, a gyroscope based or other attitude-determination subsystem, and a computer running altimetric and/or obstruction-detection software. From the digitized video data, the altimetric software computes the pixel velocity in an appropriate part of the video image and the corresponding angular relative motion of the ground within the field of view of the camera. Then by use of trigonometric relationships among the aircraft velocity, the attitude of the camera, the angular relative motion, and the altitude, the software computes the altitude. The obstruction-detection software performs somewhat similar calculations as part of a larger task in which it uses the pixel velocity data from the entire video image to compute a depth map, which can be correlated with a terrain map, showing locations of potential obstructions. The depth map can be used as real-time hazard display and/or to update an obstruction database.

Delgado, Frank J.↗
NASA NTRS2013

Scalable Adaptive Graphics Environment (SAGE) Software for the Visualization of Large Data Sets on a Video Wall

The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of "big data" available from new high resolution remote sensing satellite sensors or four‐dimensional numerical model simulations is propelling the wider adoption of ultra‐resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well‐integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Shortterm Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display‐to‐dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data‐intensive information. This information can be digital‐cinema animations, high‐resolution images, high‐definition video‐teleconferences, presentation slides, documents, spreadsheets or laptop screens. SAGE is cross‐platform, community‐driven, open‐source visualization and collaboration middleware that utilizes shared national and international cyberinfrastructure for the advancement of scientific research and education.

Jedlovec, Gary↗
DOE OSTI2025

House Advantage or House of Cards? Stacking the Deck for Data Videos Leads to Null Results: Preprint

Videos are becoming a ubiquitous means of sharing information on social media platforms. In response, data videos - short clips combining visualization with dynamic storytelling, audio descriptions, and spatial referencing - have gained popularity for communicating data. These affordances suggest that data videos might communicate data patterns, trends, and concepts more effectively than static visualizations, enhancing comprehension. However, existing research has not systematically tested this claim. To address this gap, we conducted three controlled studies to measure comprehension differences between data videos and static visualizations. Despite leveraging visual cues and audio explanations, no data video led to significantly better comprehension than an analogous static visualization. Our results suggest data videos are not categorically better and that future research should examine the tradeoffs between their engagement benefits and costs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Measured air quality impacts after teaching parents about cooking ventilation with a video: a pilot study

BackgroundCooking-related emissions contribute to air pollutants in the home and may influence children’s health outcomes.ObjectiveIn this pilot study, we investigate the effects of a cooking ventilation intervention in homes with gas stoves, including a video-based educational intervention and range hood replacement (when needed) in children’s homes.MethodsThis was a pilot (n = 14), before-after trial (clinicaltrials.gov #NCT04464720) in homes in the San Francisco Bay Area that had a school-aged child, a gas stove, and either a venting range hood or over-the-range microwave/hood. Cooking events, ventilation use, and indoor air pollution were measured in homes for 2–4 weeks, and children completed respiratory assessments. Midway, families received this intervention: (1) education about the hazards of cooking-related pollutants and benefits of both switching to back burners and using the range hood whenever cooking and (2) ensuring the range hood met airflow and sound performance standards. The educational intervention was delivered via a video developed in conjunction with local youth.ResultsWe found substantially increased use of back burners and slight increases in range hood use during cooking after intervening. Even though there was no change in cooking frequency or duration, these behavior changes resulted in decreases in nitrogen dioxide (NO2), including significant decreases in the total integrated concentration of NO2 over all cooking events from 1230 ppb*min (IQR 336, 7861) to 756 (IQR 84.0, 4210; p < 0.05) and NO2 collected on samplers over the entire pre- and post-intervention intervals from 10.4 ppb (IQR 3.5, 47.5) to 9.4 (IQR 3.0, 36.1; p < 0.005). There were smaller changes in PM2.5, and no changes were seen in respiratory outcomes.ImpactThis pilot before-after trial evaluated the use of a four-minute educational video to improve cooking ventilation in homes with gas stoves and one or more school-aged children. Participant behavior changed after watching the video, and there were decreases in indoor air pollutant concentrations in the home, some of which were significant. This brief video is now publicly available in English and Spanish (wspehsu.ucsf.edu/projects/indoor-air-quality), and this provides suggestive evidence of the utility of this simple intervention, which could be particularly beneficial for households that have children with asthma.

Holm, Stephanie M↗
NASA NTRS1974

Automated analysis of video data

A software/hardware system designed and developed to perform automated video imagery analysis is described. Major elements included in the analysis system are: (1) sampling oscilloscope; (2) programmable trigger unit; (3) central computer; and (4) software processing library. The function of the scope and trigger unit, in conjunction with the control computer, is to digitize the selected portion of the video image and store as amplitude and time data in computer memory. Evaluation of the video data, analogus to interpretation of a visual image, is accomplished by the processing software. It is indicated that this technique of video image analysis is applicable to a wide variety of nonaerospace applications involving video data and image analysis.

Hafner, D. J.↗
NASA NTRS1985

Television camera video level control system

A video level control system is provided which generates a normalized video signal for a camera processing circuit. The video level control system includes a lens iris which provides a controlled light signal to a camera tube. The camera tube converts the light signal provided by the lens iris into electrical signals. A feedback circuit in response to the electrical signals generated by the camera tube, provides feedback signals to the lens iris and the camera tube. This assures that a normalized video signal is provided in a first illumination range. An automatic gain control loop, which is also responsive to the electrical signals generated by the camera tube 4, operates in tandem with the feedback circuit. This assures that the normalized video signal is maintained in a second illumination range.

Kravitz, M.↗