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At least 73 records · Page 4

Study and simulation of spatial video compression for remotely piloted vehicles

Techniques of video compression applicable to remotely piloted vehicles (RPVs) are investigated. One approach is to reduce the frame rate, the other is to reduce the number of bits per sample needed to represent static picture detail by means of digital video compression. Hadamard transforms of 8 x 8 subpictures, with adaptive and nonadaptive quantization of transform coefficients, were investigated for the latter technique. Tapes of typical RPV video, processed by Aeronautronic Ford to simulate four frame rates, were again processed by the Ames real-time video system to obtain a variety of compressions of each of the four frame rates.

Knauer, S.↗

Biocybernetic Control of Vigilance Task Parameters

The major focus of the present proposal was to examine psychophysiological variables that are related to hazardous states of awareness induced by monitoring automated systems. With the increased use of automation in today's work environment, people's roles in the work place are being redefined from that of active participant to one of passive monitor. Although the introduction of automated systems has a number of benefits, there are also a number of disadvantages regarding the worker performance. Byrne and Parasuraman (1996) have argued for the use of psychophysiological measures in both the development and the implementation of adaptive automation. While both performance based and model based adaptive automation have been studied, the use of psychophysiological measures, especially EEG, offers the advantage of real time evaluation of the state of the subject. Previous investigations of the closed-loop adaptive automation system in our laboratory, supported by NASA, have employed a compensatory tracking task which involved the use of a joystick to maintain the position of a cursor in the middle of a video screen. This research demonstrated that, in an adaptive automation, closed-loop environment, subjects perform a tracking task better under a negative, compared to a positive, feedback condition. While tracking is comparable to some aspects of flying an airplane, it does not simulate the environment found in the cockpit of modern commercial airplanes. Since a large part of the flying responsibilities in commercial airplanes is automated, the primary responsibility of pilots is to monitor the automation and to respond when the automation fails. Because failures are relatively rare, pilots often suffer from hazardous states of awareness induced by long term vigilance of the automated system. Consequently, the aim of the current study was to investigate the ability of the closed-loop, adaptive automation system in a vigilance paradigm. It is also important to note that tracking involves a continuous, though low level, motor response. Since it is not clear how such activity might affect performance of the adaptive automation system, it was thought to be important to evaluate how the system functioned when there was minimal motor output by the subjects. The current study used the closed-loop system, developed at NASA-Langley Research Center, to control the state of awareness of subjects while they performed a vigilance task. Several experiments were conducted to examine the use of EEG feedback to control a target dimension used in the task. Changes in a subject's arousal, as defined by specific EEG indexes, produced stimulus changes known to affect task performance. In addition, different electrode sites, compared to previous research, were sampled to determine the optimum configuration with regard to the following criteria: (1) task performance and (2) EEG index.

Freeman, Frederick G.↗

Virtual Reality for Shoot/No-Shoot Decision Training in Law Enforcement: A Literature Review and Research Agenda

Virtual reality (VR) can materially improve “shoot / no-shoot” (SNS) training by giving officers realistic, repeatable practice making high-stakes decisions under pressure. Traditional tools—live-fire ranges and video simulators—build basics, but they cannot adapt to each officer in real time or fully mirror the complexity of the field. VR closes that gap by creating immersive scenarios that are safer, more flexible, easier to scale across units, and able to capture objective performance data. SNS decisions are not just about marksmanship; they rely on perception, judgment, memory, and the ability to hold fire when a threat is uncertain. Effective training therefore needs realism, decision complexity, and branching outcomes that reflect the true consequences of choices. These elements strengthen recognition of hostile intent while reducing false positives and building the self-control required in ambiguous situations. VR brings specific advantages: dynamic environments, full-body interaction, and the ability to measure performance with precision—enabling targeted feedback and better transfer of learning to the street. At the same time, responsible deployment must address scenario quality (credible environments and behaviors), lawful decision models, and user wellbeing (appropriate stress levels, comfort, and safety). Sandia’s VIPER Lab is positioned to lead this work. The team combines human-performance science, AI/ML, and VR/AR development with a deep equipment bench (e.g., omnidirectional treadmill, eye-tracking, haptics, multiple HMDs). This ecosystem supports building and validating next-generation SNS training that is immersive, measurable, and trustworthy. Bottom line: Investment in VR-enabled SNS training that blends evidence-based design with careful validation and legal safeguards is expected to pay off in safer, more consistent decision-making and improved community trust, delivered through training that is practical to deploy at scale.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Modular on-board adaptive imaging

Feature extraction involves the transformation of a raw video image to a more compact representation of the scene in which relevant information about objects of interest is retained. The task of the low-level processor is to extract object outlines and pass the data to the high-level process in a format that facilitates pattern recognition tasks. Due to the immense computational load caused by processing a 256x256 image, even a fast minicomputer requires a few seconds to complete this low-level processing. It is, therefore, necessary to consider hardware implementation of these low-level functions to achieve real-time processing speeds. The considered project had the objective to implement a system in which the continuous feature extraction process is not affected by the dynamic changes in the scene, varying lighting conditions, or object motion relative to the cameras. Due to the high bandwidth (3.5 MHz) and serial nature of the TV data, a pipeline processing scheme was adopted as the overall architecture of this system. Modularity in the system is achieved by designing circuits that are generic within the overall system.

Eskenazi, R.↗

Learning the Temporal Effect in Infrared Thermal Videos With Long Short-Term Memory for Quality Prediction in Resistance Spot Welding

With the advances of sensing technology, in-situ infrared thermal videos can be collected from Resistance Spot Welding (RSW) processes. Each video records the formulation process of a weld nugget. The nugget evolution creates a “temporal effect” across the frames, which can be leveraged for real-time, nondestructive evaluation (NDE) of the weld quality. Currently, quality prediction with imaging data mainly focuses on optical feature extraction with Convolutional Neural Network (CNN) but does not make the most of such temporal effect. In this study, pixels corresponding to critical locations on the weld nugget surface are extracted from a video to form multivariate time series (MTS). Multivariate Adaptive Regression Splines (MARS) is used in MTS processing to remove noisy signals related to uninformative frames. A Stacked Long Short-Term Memory (LSTM) model is developed to learn from the processed MTS and then predicts weld nugget size and thickness in real-time NDE. Results from a case study on RSW of Boron steel demonstrates the improvement in prediction accuracy and computational time with the proposed method, as compared to CNN-based weld quality prediction.

Guo, Shenghan↗

Quality metrics for sensor images

Methods are needed for evaluating the quality of augmented visual displays (AVID). Computational quality metrics will help summarize, interpolate, and extrapolate the results of human performance tests with displays. The FLM Vision group at NASA Ames has been developing computational models of visual processing and using them to develop computational metrics for similar problems. For example, display modeling systems use metrics for comparing proposed displays, halftoning optimizing methods use metrics to evaluate the difference between the halftone and the original, and image compression methods minimize the predicted visibility of compression artifacts. The visual discrimination models take as input two arbitrary images A and B and compute an estimate of the probability that a human observer will report that A is different from B. If A is an image that one desires to display and B is the actual displayed image, such an estimate can be regarded as an image quality metric reflecting how well B approximates A. There are additional complexities associated with the problem of evaluating the quality of radar and IR enhanced displays for AVID tasks. One important problem is the question of whether intruding obstacles are detectable in such displays. Although the discrimination model can handle detection situations by making B the original image A plus the intrusion, this detection model makes the inappropriate assumption that the observer knows where the intrusion will be. Effects of signal uncertainty need to be added to our models. A pilot needs to make decisions rapidly. The models need to predict not just the probability of a correct decision, but the probability of a correct decision by the time the decision needs to be made. That is, the models need to predict latency as well as accuracy. Luce and Green have generated models for auditory detection latencies. Similar models are needed for visual detection. Most image quality models are designed for static imagery. Watson has been developing a general spatial-temporal vision model to optimize video compression techniques. These models need to be adapted and calibrated for AVID applications.

Ahumada, AL↗

An adaptive algorithm for motion compensated color image coding

This paper presents an adaptive algorithm for motion compensated color image coding. The algorithm can be used for video teleconferencing or broadcast signals. Activity segmentation is used to reduce the bit rate and a variable stage search is conducted to save computations. The adaptive algorithm is compared with the nonadaptive algorithm and it is shown that with approximately 60 percent savings in computing the motion vector and 33 percent additional compression, the performance of the adaptive algorithm is similar to the nonadaptive algorithm. The adaptive algorithm results also show improvement of up to 1 bit/pel over interframe DPCM coding with nonuniform quantization. The test pictures used for this study were recorded directly from broadcast video in color.

Kwatra, Subhash C.↗

A constrained joint source/channel coder design and vector quantization of nonstationary sources

The emergence of broadband ISDN as the network for the future brings with it the promise of integration of all proposed services in a flexible environment. In order to achieve this flexibility, asynchronous transfer mode (ATM) has been proposed as the transfer technique. During this period a study was conducted on the bridging of network transmission performance and video coding. The successful transmission of variable bit rate video over ATM networks relies on the interaction between the video coding algorithm and the ATM networks. Two aspects of networks that determine the efficiency of video transmission are the resource allocation algorithm and the congestion control algorithm. These are explained in this report. Vector quantization (VQ) is one of the more popular compression techniques to appear in the last twenty years. Numerous compression techniques, which incorporate VQ, have been proposed. While the LBG VQ provides excellent compression, there are also several drawbacks to the use of the LBG quantizers including search complexity and memory requirements, and a mismatch between the codebook and the inputs. The latter mainly stems from the fact that the VQ is generally designed for a specific rate and a specific class of inputs. In this work, an adaptive technique is proposed for vector quantization of images and video sequences. This technique is an extension of the recursively indexed scalar quantization (RISQ) algorithm.

Sayood, Khalid↗

Analog video magnetograms in real time.

Description of a video differential photometer which is the result of an attempt to adapt television technology to the task of producing an electronic equivalent of the photographic subtraction technique. Advantages of electronic subtraction are potentially greater field sensitivity, immediate availability of the subtracted magnetograms (virtually in real time), and greater versatility in combining and comparing image data. Commercial television equipment was used in construction of the apparatus. All video subtraction, averaging, and other processing is done in analog form. The final magnetogram is displayed on an ordinary television monitor.

Smithson, R. C.↗

Real-Time Compression Of Digital Video

Enhanced DPCM video compression algorithm utilizes non-uniform quantizer, non-adaptive predictor, and multi-level Huffman coder to substantially reduce data rate below that achievable with conventional DPCM. Images reconstructed without noticeable degradation.

Bizon, Thomas P.↗

Orbital Communications Adapter

What is OCA? The OCA system provides the capability to transfer data (documents, imagery, video, data) between a ground PC network in MCC-H and the onboard SSC and JSL systems via Ku band.

Michelle Lee Nowling↗

Airflow Research

This is an overview of research being done in laminar flow at Ames Dryden Flight Research Center and Langley Research Center. Airflow research at Ames Dryden has resulted in a special wing covering that will artificially induce laminar flow on the wing surface; this specially adapted wing is shown being tested in different flying conditions. This video also features research done at Langley in producing a chemical covering for wings that will make visible natural laminar flow and turbulent airflow patterns as they occur. Langley researchers explain possible use of this technology in supersonic flight.

Source record↗

New Directions in Space Operations Services in Support of Interplanetary Exploration

To gain access to the necessary operational processes and data in support of NASA's Lunar/Mars Exploration Initiative, new services, adequate levels of computing cycles and access to myriad forms of data must be provided to onboard spacecraft and ground based personnel/systems (earth, lunar and Martian) to enable interplanetary exploration by humans. These systems, cycles and access to vast amounts of development, test and operational data will be required to provide a new level of services not currently available to existing spacecraft, on board crews and other operational personnel. Although current voice, video and data systems in support of current space based operations has been adequate, new highly reliable and autonomous processes and services will be necessary for future space exploration activities. These services will range from the more mundane voice in LEO to voice in interplanetary travel which because of the high latencies will require new voice processes and standards. New services, like component failure predictions based on data mining of significant quantities of data, located at disparate locations, will be required. 3D or holographic representation of onboard components, systems or family members will greatly improve maintenance, operations and service restoration not to mention crew morale. Current operational systems and standards, like the Internet Protocol, will not able to provide the level of service required end to end from an end point on the Martian surface like a scientific instrument to a researcher at a university. Ground operations whether earth, lunar or Martian and in flight operations to the moon and especially to Mars will require significant autonomy that will require access to highly reliable processing capabilities, data storage based on network storage technologies. Significant processing cycles will be needed onboard but could be borrowed from other locations either ground based or onboard other spacecraft. Reliability will be a key factor with onboard and distributed backup processing an absolutely necessary requirement. Current cluster processing/Grid technologies may provide the basis for providing these services. An overview of existing services, future services that will be required and the technologies and standards required to be developed will be presented. The purpose of this paper will be to initiate a technological roadmap, albeit at a high level, of current voice, video, data and network technologies and standards (which show promise for adaptation or evolution) to what technologies and standards need to be redefined, adjusted or areas where new ones require development. The roadmap should begin the differentiation between non manned and manned processes/services where applicable. The paper will be based in part on the activities of the CCSDS Monitor and Control working group which is beginning the process of standardization of the these processes. Another element of the paper will be based on an analysis of current technologies supporting space flight processes and services at JSC, MSFC, GSFC and to a lesser extent at KSC. Work being accomplished in areas such as Grid computing, data mining and network storage at ARC, IBM and the University of Alabama at Huntsville will be researched and analyzed.

Bradford, Robert N.↗

An Incremental Tensor Train Decomposition Algorithm

We present a new algorithm for incrementally updating the tensor train decomposition of a stream of tensor data. This new algorithm, called the tensor train incremental core expansion (TT-ICE) improves upon the current state-of-the-art algorithms for compressing in tensor train format by developing a new adaptive approach that incurs significantly slower rank growth and guarantees compression accuracy. This capability is achieved by limiting the number of new vectors appended to the TT-cores of an existing accumulation tensor after each data increment. These vectors represent directions orthogonal to the span of existing cores and are limited to those needed to represent a newly arrived tensor to a target accuracy. We provide two versions of the algorithm: TT-ICE and TT-ICE accelerated with heuristics (TT-ICE*). Here, we provide a proof of correctness for TT-ICE and empirically demonstrate the performance of the algorithms in compressing large-scale video and scientific simulation datasets. Compared to existing approaches that also use rank adaptation, TT-ICE* achieves 57× higher compression and up to 95% reduction in computational time.

97 MATHEMATICS AND COMPUTING↗

Producing two-dimensional dust clouds and clusters using a movable electrode for complex plasma and fundamental physics experiments

We report a Bidirectional Electrode Control Arm Assembly (BECAA) for precisely manipulating dust clouds levitated above the powered electrode in RF plasmas. The reported techniques allow the creation of perfectly 2D dust layers by eliminating off-plane particles by moving the electrode from outside the plasma chamber without altering the plasma conditions. Here, the tilting and moving of electrodes using BECAA also allows the precise and repeatable elimination of dust particles one by one to achieve any desired number of grains N without trial and error. Simultaneously acquired top and side view images of dust clusters show that they are perfectly planar or 2D. A demonstration of clusters with N = 1–28 without changing the plasma conditions is presented to show the utility of BECAA for complex plasma and statistical physics experimental design. Demonstration videos and 3D printable part files are available for easy reproduction and adaptation of this new method to repeatably produce 2D clusters in existing RF plasma chambers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Behavioral Adaptations of Female Mice on the International Space Station

Adult female mice were sent to the International Space Station (ISS) as part of an early life science mission utilizing NASA's Rodent Habitat. Its primary purpose was to provide further insight into the influence of a microgravity environment on various aspects of mammalian physiology and well-being as part of an ongoing program of research aimed ultimately at understanding and ameliorating the deleterious influences of space on the human body. The present study took advantage of video collected from fixed, in-flight cameras within the habitat itself, to assess behavioral adaptations observed among in-flight mice aboard the ISS and differences in behavior with respect to a control group on the ground. Data collection consisted of several behavioral measures recorded by a trained observer with the assistance of interactive behavior analysis software. Specific behavioral measures included frequencies of conspecific interactionsociability, time spent feeding and conducting hygienic behavior, and relative durations of thigmotactic behavior, which is commonly used as an index of anxiety. Data were used to test tentative hypotheses that such behaviors differ significantly across mice under microgravity versus 1g conditions, and the assumption that the novel experience of microgravity itself may represent an initially anxiogenic stimulus which an animal will eventually acclimate to, perhaps through habituation.

Behavior in space↗