Results for “videos”

DOE OSTI2018

Spatiotemporal video-domain high-fidelity simulation and realistic visualization of full-field dynamic responses of structures by a combination of high-spatial-resolution modal model and video motion manipulations

Structures with complex geometries, material properties, and boundary conditions exhibit spatially local dynamic behaviors. A high-spatial-resolution model of the structure is thus required for high-fidelity analysis, assessment, and prediction of the dynamic phenomena of the structure. The traditional approach is to build a highly refined finite element computer model for simulating and analyzing the structural dynamic phenomena based on detailed knowledge and explicit modeling of the structural physics such as geometries, materials properties, and boundary conditions. These physics information of the structure may not be available or accurately modeled in many cases, however. In addition, the simulation on the high-spatial-resolution structural model, with a massive number of degrees of freedom and system parameters, is computationally demanding. Here this study, on a proof-of-principle basis, proposes a novel alternative approach for spatiotemporal video-domain high-fidelity simulation and realistic visualization of full-field structural dynamics by an innovative combination of the fundamentals of structural dynamic modeling and the advanced video motion manipulation techniques. Specifically, a low-modal-dimensional yet high-spatial (pixel)-resolution (as many spatial points as the pixel number on the structure in the video frame) modal model is established in the spatiotemporal video domain with full-field modal parameters first estimated from line-of-sight video measurements of the operating structure. Then in order to simulate new dynamic response of the structure subject to a new force, the force is projected onto each modal domain, and the modal response is computed by solving each individual single-degree-of-freedom system in the modal domain. The simulated modal responses are then synthesized by the full-field mode shapes using modal superposition to obtain the simulated full-field structural dynamic response. Finally, the simulated structural dynamic response is embedded into the original video, replacing the original motion of the video, thus generating a new photo-realistic, physically accurate video that enables a realistic, high-fidelity visualization/animation of the simulated full-field vibration of the structure. Laboratory experiments are conducted to validate the proposed method, and the error sources and limitations in practical implementations are also discussed. Compared with high-fidelity finite element computer model simulations of structural dynamics, the video-based simulation method removes the need to explicitly model the structure's physics. In addition, the photo-realistic, physically accurate simulated video provides a realistic visualization/animation of the full-field structural dynamic response, which was not traditionally available. Lastly, these features of the proposed method should enable a new alternative to the traditional computer-aided finite element model simulation for high-fidelity simulating and realistically visualizing full-field structural dynamics in a relatively efficient and user-friendly manner.

42 ENGINEERING↗

NASA NTRS1993

A prototype to automate the video subsystem routing for the video distribution subsystem of Space Station Freedom

The Video Distribution Subsystem (VDS) for Space Station Freedom provides onboard video communications. The VDS includes three major functions: external video switching; internal video switching; and sync and control generation. The Video Subsystem Routing (VSR) is a part of the VDS Manager Computer Software Configuration Item (VSM/CSCI). The VSM/CSCI is the software which controls and monitors the VDS equipment. VSR activates, terminates, and modifies video services in response to Tier-1 commands to connect video sources to video destinations. VSR selects connection paths based on availability of resources and updates the video routing lookup tables. This project involves investigating the current methodology to automate the Video Subsystem Routing and developing and testing a prototype as 'proof of concept' for designers.

Betz, Jessie M. Bethly↗

NASA NTRS1991

A video event trigger for high frame rate, high resolution video technology

When video replaces film the digitized video data accumulates very rapidly, leading to a difficult and costly data storage problem. One solution exists for cases when the video images represent continuously repetitive 'static scenes' containing negligible activity, occasionally interrupted by short events of interest. Minutes or hours of redundant video frames can be ignored, and not stored, until activity begins. A new, highly parallel digital state machine generates a digital trigger signal at the onset of a video event. High capacity random access memory storage coupled with newly available fuzzy logic devices permits the monitoring of a video image stream for long term or short term changes caused by spatial translation, dilation, appearance, disappearance, or color change in a video object. Pretrigger and post-trigger storage techniques are then adaptable for archiving the digital stream from only the significant video images.

Williams, Glenn L.↗

DOE OSTI2022

3DBFSVBF (3D BatFinder Smart Video BioFilter and Multi-class BatFinder Smart Video BioFilter) [SWR-22-88]

Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source 3D computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The machine learning has been trained on 3D data and allows for automated real-time data collection, identification and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. This machine learning model is an added feature to the previous BatFinder Smart Video BioFilter and increases the accuracy of that systems classification by increasing the accuracy of identifying bats (90% accuracy) and insects (69% accuracy) to a 97% accuracy. There are two object classifier machine learning models, Binary and multi-classification. Binary object classifier labeled BatFinder_Smart_Video_BioFilter.h5 distinguishes between biological objects and non-biological objects. The main goal of this object classifier is to ignore the turbine blades while detecting biological object flying withing the rotor swept area of the turbine. Non-biological objects have a probability of 0 and biological objects have a probability of 1. Multi-classifier labeled Multiclass_BatFinder_Smart_Video_BioFilter.h5 distinguishes between bats, birds, insects and non-biological.

Yarbrough, John↗

DOE OSTI2019

Estimation of full-field dynamic strains from digital video measurements of output-only beam structures by video motion processing and modal superposition

Strain is an necessary quantity to characterize local structural behaviors and directly correlates with structural damage initiation and development that is within local regions. Strain measurement at high spatial resolution (density) locations is thus required to characterize local structural behaviors and detect potential local damage. Traditional contact-type strain gauges are mostly discrete point-wise sensors that can only be placed in a limited number of positions. Distributed optical fiber sensing techniques can measure strains at spatially dense measurement points, but their instrumentation is a time- and labor-intensive process associated with the issue of the fragility of fibers. Noncontact optical measurement techniques, such as a family of interferometry techniques using laser beams (e.g., laser Doppler vibrometers), can provide vibration measurement at high density spatial points without the need to install sensors on the structure. Yet, these measurement devices are active sensing methods that are relatively expensive and vulnerable to ambient motion. Photogrammetry is an alternative noncontact optical measurement method using (passive) white-light imaging of digital video cameras that are relatively low-cost, agile, and provides simultaneous measurements at high spatial density locations where every pixel becomes a measurement point. Among others, digital image correlation can achieve full-field deformation measurements and subsequently estimate the full-field strains. However, it is computationally extensive. This research develops a new efficient approach to estimate the full-field (as many measurement points as the pixel number of the video frame on the structure) dynamic strains at high-spatial (pixel)-resolution/density location points from the digital video measurement of output-only vibrating structures. The developed approach is based on phase-based video motion estimation and modal superposition of structural dynamic response. Moreover, the method is augmented by a high-fidelity finite element model, which is updated with the full-field experimental modal parameters “blindly” identified from the video measurement of the output-only structure. Laboratory experiments are conducted to validate the method on a bench-scale cantilever beam structure. Results demonstrate that the full-field dynamic strain estimated by the developed approach from the video measurement of the output-only vibrating beam match very well those directly measured by the strain gauges (at discrete measurement points). Some factors associated with the effectiveness of the method are experimentally studied and discussed.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Videos, photos, and AI-derived grain size data associated with “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization” under review. This data package includes five data types: 1) raw photos and videos from drone survey and walking smartphone surveys; 2) images derived from raw videos; 3) manual labeling of reference scales; 4) metadata for all images and photo resolution derived from artificial intelligence (AI) models or manual labels, 5) grain size data obtained from AI models for all photos, 6) metadata and grain size data after quality control, 7) summaries of sample efficiency for all data, and 8) computational fluid dynamics (CFD) data used to support hydro-biogeochemical (HBGC) parameter estimation. Such data is used to 1) demonstrate significant improvements in accuracy, efficiency, and quality control for grain size data collection with the help of AI models, 2) study the spatial heterogeneity of grain size and observation reproducibility based on tens of thousands of data points generated by the AI models, and 3) evaluate the impacts of grain size heterogeneity on key HBGC parameters across sediment-to-reach and hourly-to-yearly scales. In particular, the data package contains 116 folders and 179696 files. The files include 41 videos in .mov format, 64047 photos in .jpg format, 13541 video-derived photos in .png format, 12747 segmentation mask data in .tif format, 12747 segmentation data in .json format, 24771 .csv files that with metadata and grain size for each individual photo as well as water depth and velocity data from CFD and observation, 51791 .txt files of raw AI predicted labels, and 11 flight record data in .srt format. The summary for all metadata and grain size statistics information is included in “Scales_V3_NG.csv” and “Statistics_V3_NG.csv”. The summary for data that pass data quality control (QC) level 0-2 is included in “QCStatistics_V3_NG.csv”. The QC level 0 represents photos whose photo resolution is positive, excluding photos that miss reference scale. The QC level 1 means reference scale circularity uncertainty is less than 5% for smartphone images while representing photo resolution is larger than 0.44 mm/pixel for drone images. The QC level 2 means excluding photos whose grain number is less than 100, a minimum number of grains recommended by classic literature. The summary for each video’s name, length, frame rates, survey area, grain number, survey efficiency, etc. can be found in “QCSummary_V3_NG.csv”. The summary for site name, GPS coordinates, and number of images at each site can be found in “SitesSummary_V3_*.csv” files. Overall computational efficiency summary is reported in Table 4 of accompanying manuscript. Additionally, the nitrate concentration data used in this work was downloaded from an existing dataset published on ESS-DIVE (Boat-Dragged Sensor Hanford Reach.csv; Conner A. et al., 2020). We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Port of Benton, and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the data were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate data collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Compact video content representation for video coding using low multi-linear tensor rank approximation with dynamic core tensor order

Tensor is a multi-way representation of an entity that is widely used in many applications of mathematics and physics. The wide range of tensor algebra operations attract the researchers of graphical and vision field to identify unique methods for various applications such as segmentation, compression, indexing and so on. In this paper, low multi-linear rank approximation of a tensor is used for decomposition so as to perform compression on a video that is represented as a 4D tensor. Thus, the encoder has blocks for (1) multilinear rank approximation method so as to aid decomposition, (2) sparsity removal of residual data to reduce the required memory storage to a small level, (3) quantization on the sparse less residual data and (4) LZ77 dictionary coding for the video. The decoder uses a tensor reconstruction block along with residual error correction block that reduces loss/error in the reconstructed video. The size of core tensor is an important factor in rank approximation. It is identified at run time depending on the video contents. This size is determined adaptively using Tikhonov’s regularization method. The best value of core tensor size is identified with the corner of L-curve which preserves the video contents from heavy loss/error. Experimental results of the proposed work on comparison with H.264/AVC compression method indicate that the proposed method achieves up to 10% improvement in compression ratio with the least amount of loss and a maximum signal to noise ratio of 0.14. The proposed system gives better compression ratio than H.265 for videos with more number of frames without compromising quality.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2002

Video Observations Encompassing the 2002 Leonid Storm: First Results and a Revised Photometric Procedure for Video Meteor Analysis

During the 2001 Leonid storm, Marshall Space Flight Center, with the cooperation of the University of Western Ontario and the United States Air Force, deployed 6 teams of observers equipped with intensified video systems to sites located in North America, the Pacific, and Mongolia. The campaign was extremely successful, with the entire period of enhanced Leonid activity (over 16 hours) captured on video tape in a consistent manner. We present the first results from the analysis of this unique, 2 terabyte data set and discuss the problems involved in reducing large amounts of video meteor data. In particular, the question of how to determine meteor masses though photometric analysis will be re-examined, and new techniques will be proposed that eliminate some of the deficiencies suffered by the techniques currently employed in video meteor analysis.

Cooke, William J.↗

NASA NTRS2002

Video Observations Encompassing the 2002 Leonid Storm: First Results and a Revised Photometric Procedure for Video Meteor Analysis

During the 2001 Leonid storm, Marshall Space Flight Center, with the cooperation of the University of Western Ontario and the United States Air Force, deployed 6 teams of observers equipped with intensified video systems to sites located in North America, the Pacific, and Mongolia. The campaign was extremely successful, with the entire period of enhanced Leonid activity (over 16 hours) captured on video tape in a consistent manner. We present the first results from the analysis of this unique, 2 terabyte data set and discuss the problems involved in reducing large amounts of video meteor data. In particular, the question of how to determine meteor masses though photometric analysis will be re-examined, and new techniques will be proposed that eliminate some of the deficiencies suffered by the techniques currently employed in video meteor analysis.

Cooke, William J.↗

DOE OSTI2022

BFSVBF (BatFinder Smart Video BioFilter) [SWR-22-87] and Multi-class BatFinder Smart Video BioFilter Keras

Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The code has gone through five rounds of development with images used to train the models. This advancement allows for automated real-time data collection, identification, and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. We will discuss the two open source and publicly available machine learning models developed within this scope of this work: 1) a binary model with a 97.5% accuracy in identifying the difference between an object and an empty scene, including wind turbine and clouds; and 2) a multiple classification model with the capability of identifying the type of object detected: bats (90% accuracy), birds (83% accuracy), insects (69% accuracy) and non-biological (99% accuracy).

Yarbrough, John↗

NASA NTRS2023

Video That's Out of This World: A Snapshot of Video Distribution from Across the Solar System

While extraterrestrial scientific research advances to the Moon and Mars, so does the need for secure high-quality video links to capture data and share the experience. This paper describes the space to ground architecture needed to satisfy the cultural mantra challenging “Pictures or it didn’t happen!” as NASA travels beyond Low Earth Orbit. The Marshall Space Flight Center’s Delay Tolerant Network Marshall Enterprise (DTNME) protocol is the framework for video distribution beyond the terrestrial Internet, appropriate for communications across the solar system. Utilizing the International Space Station (ISS) as a test facility, NASA engineers and contractors will demonstrate new technologies and capabilities to transmit high-quality video imagery for NASA’s return to the Moon, Mars exploration, and next generation of explorers.

Photography↗

NASA NTRS2023

Video That's Out of This World: A Snapshot of Video Distribution from Across the Solar System

While extraterrestrial scientific research advances to the Moon and Mars, so does the need for secure high-quality video links to capture data and share the experience. This paper describes the space to ground architecture needed to satisfy the cultural mantra challenging “Pictures or it didn’t happen!” as NASA travels beyond Low Earth Orbit. The Marshall Space Flight Center’s Delay Tolerant Network Marshall Enterprise (DTNME) protocol is the framework for video distribution beyond the terrestrial Internet, appropriate for communications across the solar system. Utilizing the International Space Station (ISS) as a test facility, NASA engineers and contractors will demonstrate new technologies and capabilities to transmit high-quality video imagery for NASA’s return to the Moon, Mars exploration, and next generation of explorers.

Photography↗

NASA NTRS2023

Video That's Out of This World: A Snapshot of Video Distribution from Across the Solar System

While extraterrestrial scientific research advances to the Moon and Mars, so does the need for secure high-quality video links to capture data and share the experience. This paper describes the space to ground architecture needed to satisfy the cultural mantra challenging “Pictures or it didn’t happen!” as NASA travels beyond Low Earth Orbit. The Marshall Space Flight Center’s Delay Tolerant Network Marshall Enterprise (DTNME) protocol is the framework for video distribution beyond the terrestrial Internet, appropriate for communications across the solar system. Utilizing the International Space Station (ISS) as a test facility, NASA engineers and contractors will demonstrate new technologies and capabilities to transmit high-quality video imagery for NASA’s return to the Moon, Mars exploration, and next generation of explorers.

Photography↗

NASA NTRS1994

Controlling telerobots with video data and compensating for time-delayed video using Omniview

Remote viewing is critical for teleoperations, but the inherent limitations of standard video reduce the operator's effectiveness. These limitations have been compensated for in many ways, from using the operator's adaptability, to augmenting his capability with feedback from a variety of sensors and simulations. Omniview can overcome some of these limitations and improve the operator's efficiency without adding additional sensors or computational burden. It can minimize the potential collisions with facility equipment, provide peripheral vision, and display multiple images simultaneously from a single input device. The Omniview technology provides electronic pan, tilt, magnify, and rotational orientation within a hemispherical field-of-view without any moving parts. Image sizes, viewing directions, scale, offset, etc., may be adjusted to fit operator needs. This paper discusses the derivation of the image transformation, the design of the electronics, and two applications to telepresence that are under development. These are Video Emulated Tweening (VET), and Manipulator Guidance and Positioning (ManGAP). The VET effort uses Omniview to compensate for time-delayed video in teleoperation of remote vehicles. In ManGAP two Omniview systems are used to provide two sets of orientation vectors to points in the field-of-view (FOV). These vectors then provide absolute position information to both control the position of the telerobot, and to avoid collisions with the work sight equipment.

Kuban, Dan↗

NASA NTRSDate not supplied

Video That's Out of This World: A Snapshot of Video Distribution from Across the Solar System

While extraterrestrial scientific research advances to the Moon and Mars, so does the need for secure high-quality video links to capture data and share the experience. This paper describes the space to ground architecture needed to satisfy the cultural mantra challenging “Pictures or it didn’t happen!” as NASA travels beyond Low Earth Orbit. The Marshall Space Flight Center’s Delay Tolerant Network Marshall Enterprise (DTNME) protocol is the framework for video distribution beyond the terrestrial Internet, appropriate for communications across the solar system. Utilizing the International Space Station (ISS) as a test facility, NASA engineers and contractors will demonstrate new technologies and capabilities to transmit high-quality video imagery for NASA’s return to the Moon, Mars exploration, and next generation of explorers.

Jennifer L. Christopher↗

DOE OSTI2016

Design and characterization of a prototype divertor viewing infrared video bolometer for NSTX-U

The InfraRed Video Bolometer (IRVB) is a powerful tool to measure radiated power in magnetically confined plasmas due to its ability to obtain 2D images of plasma emission using a technique that is compatible with the fusion nuclear environment. A prototype IRVB has been developed and installed on NSTX-U to view the lower divertor. The IRVB is a pinhole camera which images radiation from the plasma onto a 2.5 μm thick, 9 × 7 cm{sup 2} Pt foil and monitors the resulting spatio-temporal temperature evolution using an IR camera. The power flux incident on the foil is calculated by solving the 2D+time heat diffusion equation, using the foil’s calibrated thermal properties. An optimized, high frame rate IRVB, is quantitatively compared to results from a resistive bolometer on the bench using a modulated 405 nm laser beam with variable power density and square wave modulation from 0.2 Hz to 250 Hz. The design of the NSTX-U system and benchtop characterization are presented where signal-to-noise ratios are assessed using three different IR cameras: FLIR A655sc, FLIR A6751sc, and SBF-161. The sensitivity of the IRVB equipped with the SBF-161 camera is found to be high enough to measure radiation features in the NSTX-U lower divertor as estimated using SOLPS modeling. The optimized IRVB has a frame rate up to 50 Hz, high enough to distinguish radiation during edge-localized-modes (ELMs) from that between ELMs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Increased accuracy and signal-to-noise ratio through recent improvements in infra-red video bolometer fabrication and calibration

The infra-red video bolometer (IRVB) is a diagnostic equipped with an infra-red camera that measures the total radiated power in thousands of lines of sight within a large field of view. Recently validated in MAST-U [Fderici et al., Rev. Sci. Instrum. 94, 033502 (2023)], it offers a high spatial resolution map of the radiated power in the divertor region, where large gradients are expected. The IRVB’s sensing element comprises a thin layer of high Z absorbing material, typically platinum, usually coated with carbon to reduce reflections [Peterson et al., Rev. Sci. Instrum. 79, 10E301 (2008)].Here, the possibility of using a relatively inert material such as titanium, is explored that can be produced in layers up to 1 μm compared to 2.5 μm for Pt and then coat it with Pt of the desired thickness (0.3 μm per side here) and carbon. This leads to a higher temperature signal (about 3 times) and better spatial resolution (about 4 times), resulting in higher accuracy in the measured power [Peterson et al., Rev. Sci. Instrum. 79, 10E301 (2008)]. This assembly is also expected to improve foil uniformity, as the Pt layer is obtained via deposition rather than mechanical processes [Mukai et al., Rev. Sci. Instrum. 87, 2014 (2016)].Given its multi-material composition, measuring the thermal properties of the foil assembly is vital. Various methods using a calibrated laser as a heat source have been developed, analyzing the temperature profile shape [Sano et al., Plasma and Fusion Res. 7, 2405039 (2012)] and [Mukai et al., Rev. Sci. Instrum. 89, 10E114 (2018)] or fitting the calculated laser power for different intensities and frequencies [Fderici et al., Rev. Sci. Instrum. 94, 033502 (2023)]. Here, a simpler approach is presented, which relies on analyzing the separate components of the foil heat equation for a single laser exposure in a given area. This can then be iterated over the entire foil to capture local deviations.

Magnetic Fusion Energy↗

NASA NTRS1975

Sequential color video to parallel color video converter

The engineering design, development, breadboard fabrication, test, and delivery of a breadboard field sequential color video to parallel color video converter is described. The converter was designed for use onboard a manned space vehicle to eliminate a flickering TV display picture and to reduce the weight and bulk of previous ground conversion systems.

Source record↗