Perceptual study of the impact of varying frame rate on motion imagery interpretability

Abstract

The development of a motion imagery (MI) quality scale, akin to the National Image Interpretibility Rating Scale (NIIRS) for still imagery, would have great value to designers and users of surveillance and other MI systems. A multiphase study has adopted a perceptual approach to identifying the main MI attributes that affect interpretibility. The current perceptual study measured frame rate effects for simple motion imagery interpretation tasks of detecting and identifying a known target. By using synthetic imagery, there was full control of the contrast and speed of moving objects, motion complexity, the number of confusers, and the noise structure. To explore the detectibility threshold, the contrast between the darker moving objects and the background was set at 5%, 2%, and 1%. Nine viewers were to detect or identify a moving synthetic "bug" in each of 288 10-second clip. We found that frame rate, contrast, and confusers had a statistically significant effect on image interpretibility (at the 95% level), while the speed and background showed no significant effect. Generally, there was a significant loss in correct detection and identification for frame rates below 10 F/s. Increasing the contrast improved detection and at high contrast, confusers did not affect detection. Confusers reduced detection of higher speed objects. Higher speed improved detection, but complicated identification, although this effect was small. Higher speed made detection harder at 1 Frame/s, but improved detection at 30 F/s. The low loss of quality at moderately lower frame rates may have implications for bandwidth limited systems. A study is underway to confirm, with live action imagery, the results reported here with synthetic.

Application of VNIIRS for target tracking

“…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]. The methods were used for performance modeling for target recognition [55,56].…”

Methodology study for development of a motion imagery quality metric

“…The tasks included detection and recognition of objects, as might be done with still imagery, and the detection and recognition of activities, which relies on the dynamic nature of motion imagery. [9] • Frame Rate: These two evaluations assessed target detection and identification and other image exploitation tasks as a function of frame rate and contrast, using both synthetic imagery and real imagery [8,9] The key findings of these evaluations are:…”

“…A number of factors were identified that had the potential to affect perceived interpretability of motion imagery: the motion of the targets, motion of the camera, GSD (spatial resolution), frame rate (temporal resolution), color, and scene complexity. These factors have been explored and characterized in a series of evaluations [6,7,8,9] • Motion and Complexity: This evaluation assessed the effects on perceived image quality of target motion, camera motion, scene complexity, and possible interactions among these factors [6,7]. • Motion and Color: This evaluation examined the effects of color, target motion, and their interactions on perceived image quality [7] • Criteria Satisfaction: Two evaluations assessed the ability of imagery analysts to perform various image exploitation tasks with motion imagery.…”

“…In exploring avenues for development of a similar metric for motion imagery, a clearer understanding of the factors that affect the perceived quality of motion imagery was needed. Several studies have explored specific aspects of this problem, such as target motion, camera motion, color, and frame rate [6,7,8]. This study examines the ability of imagery analysts to assess the interpretability of motion imagery and assess their confidence in performing specific image exploitation tasks.…”

Quantifying Interpretability Loss due to Image Compression

“…The evaluations indicated that target motion has a significant positive effect on perceived image quality, whereas camera motion has a barely discernable effect.  Frame Rate: These evaluations assessed object detection and identification and other image exploitation tasks as a function of frame rate and contrast (Fenimore et al 2006). The study demonstrated that an analyst's ability to detect and recognize objects of interest degrades at frame rates below 15 frames per second.…”