Feasibility Study for the Development of a Motion Imagery Quality Metric

Irvine, John; Fenimore, C.P.; Cannon, David M.; Roberts, John W.; Israel, Steven A.; Simon, Larry; Watts, C.; Miller, James D.; Brennan, Michelle; Avilés, Ana Ivelisse; Tighe, Paul F.; Behrens, Richard

doi:10.1109/aipr.2004.25

Cited by 10 publications

(6 citation statements)

References 2 publications

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“…4,5,6,7,8,9 A clear conclusion was, "the ability to perform exploitation tasks depends primarily on the spatial resolution". 7 These studies also showed that trained analysts can consistently rank motion imagery based on perceived interpretability, and that analyst self-estimate of task confidence can be used as a surrogate for actual task performance. 9 Like NIIRS, each V-NIIRS level represents a power-of-two change in Ground Sample Distance (GSD).…”

Section: Niirs Backgroundmentioning

confidence: 97%

“…Previous studies have shown, "visible NIIRS ratings for the motion imagery clips are slightly, but statistically significantly, higher than for the corresponding NIIRS ratings of the still images." 3 The small increase of 1/4 NIIRS could be due to the angular diversity that occurs during the clip which increases the total number of pixels-on-target; it could also be due to a type of superresolution processing effect that occurs in the brain when viewing motion imagery that exploits recently viewed previous perspectives.…”

Section: Content Validity Of V-niirsmentioning

confidence: 97%

“…3 Subsequent work examined the effects of frame rate, laid out a methodology for development of a motion quality metric, and conducted evaluations using static and dynamic criteria. 4,5,6,7,8,9 A clear conclusion was, "the ability to perform exploitation tasks depends primarily on the spatial resolution". 7 These studies also showed that trained analysts can consistently rank motion imagery based on perceived interpretability, and that analyst self-estimate of task confidence can be used as a surrogate for actual task performance.…”

Section: Niirs Backgroundmentioning

confidence: 99%

See 2 more Smart Citations

Video National Imagery Interpretability Rating Scale criteria survey results

Young

Yen

Petitti

et al. 2009

Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VI

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The Video National Imagery Interpretability Rating Standard (V-NIIRS) consists of a ranked set of subjective criteria to assist analysts in assigning an interpretability quality level to a motion imagery clip. The V-NIIRS rating standard is needed to support the tasking, retrieval, and exploitation of motion imagery. A criteria survey was conducted to yield individual pair-wise criteria rankings and scores. Statistical analysis shows good agreement with expectations across the 9-levels of interpretability, for each of the 7 content domains.

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Section: Niirs Backgroundmentioning

confidence: 97%

Section: Content Validity Of V-niirsmentioning

confidence: 97%

Section: Niirs Backgroundmentioning

confidence: 99%

See 1 more Smart Citation

Video National Imagery Interpretability Rating Scale criteria survey results

Young

Yen

Petitti

et al. 2009

Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VI

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show abstract

“…Initial derivations were done by Irvine et al [48,49,50,51] to lay a foundation for a motion imagery quality metric that utilized the NIIRS ground sampling distance. They looked at the varying frame rate [52], perceived interpretability [53], and eventually the interpretability scale [54].…”

Section: Vniirsmentioning

confidence: 99%

Application of VNIIRS for target tracking

Blasch¹,

Kahler²

2015

SPIE Proceedings

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The Motion Imagery Standards Board (MISB) has created the Video National Imagery Interpretability Rating Scale (V-NIIRS). VNIIRS extends NIIRS to scene characterization from streaming video to include object recognition of various targets for a given size. To apply VNIIRs for target tracking, there is a need to understand the operating conditions of the sensor type, environmental phenomenon, and target behavior (SET). In this paper, we explore VNIIRS for target tracking given the sensor resolution to support the relative tracking performance using track success. The relative assessment can be used in relation to the absolute target size associated with the VNIIRS. In a notional analysis, we determine the issues and capabilities of using VNIIRS video quality ratings to determine track success. The outcome of the trade study is an experiment to understand how to use VNIIRS can support target tracking evaluation.

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“…Part of this effort is intended to contribute to the development of a formula for prediction of interpretability based on motion imagery characteristics [1]. For the NIST project, physical measures are needed to verify the motion image characteristics of the video being presented to human viewers, and to determine whether the system playback performance is sufficient to meet the needs of the tests (which is particularly important when working with high definition (HD) and high frame rate formats, and with content that stresses system performance).…”

Section: Introductionmentioning

confidence: 99%

Cross-display-technology video motion measurement tools

2006

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High performance video places severe demands on playback system and display device resources. Motion playback errors such as irregular motion playback and image breakup are common, making accurate measurement of motion critically important for device selection and system tuning to ensure the desired viewing experience. Direct observation of the actual displayed image (screen capture) is the only way to perform a complete end-to-end system test that accounts for all possible sources of motion errors, including original video capture, compression/decompression, playback system performance, and display device operation. Unfortunately for the development of measurement techniques, the fundamentally different ways that different display technologies present imagery can easily confound sensitive measurement techniques, producing measured playback performance differences across multiple display technologies such as LCD (liquid crystal display), plasma, CRT (cathode ray tube), and DMD (digital micromirror device) that are disproportionately large compared to the actual differences (if any) seen by a human viewer. Crosstechnology measurement tools are necessary to ensure the validity of measures across multiple technologies. The methods being used include a combination of test materials (both selected live video clips and synthetic clips), capture technique (including control of capture rate, triggering, and timestamping), and analysis. This paper describes these methods, then gives several illustrative examples of the use of these methods by the project. The NIST Motion Image Quality Measurement project uses a combination of quantitative measures and subjective analysis to evaluate motion imagery and to identify the factors that determine overall performance. The NIST project has conducted tests to measure (1) perceived image quality and (2) motion image interpretability, as a function of factors including compression, video motion and other scene content, playback system performance, and frame rate. Tests have been conducted using a variety of playback systems with different levels of performance, and using a variety of display technologies. BACKGROUNDNIST is developing new ways to measure the motion characteristics of video playback, as seen by the human viewer. The ability to perform such measurement is important for designing and configuring systems, and authoring content. By definition, motion image quality relates to what a human viewer can see (a subjective response). It is important, however, to be able to produce repeatable numeric measurements (an objective response), to compensate for variations among human viewers and to allow accurate modeling of system performance, for example when tuning a system to meet a given set of requirements. The NIST team has found instances in which the different characteristics of different display technologies, such as LCD, plasma, CRT, or DMD, produce results that look very similar to the human eye, but that are rated very differently from one another using a specific screen ca...

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Feasibility Study for the Development of a Motion Imagery Quality Metric

Cited by 10 publications

References 2 publications

Video National Imagery Interpretability Rating Scale criteria survey results

Video National Imagery Interpretability Rating Scale criteria survey results

Application of VNIIRS for target tracking

Cross-display-technology video motion measurement tools

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