Target Acquisition Performance Research Articles

Target acquisition performance in the presence of JPEG image compression

This paper presents an investigation on the effect of JPEG compression on the similarity between the target image and the background, where the similarity is further used to determine the degree of clutter in the image. Four new clutter metrics based on image quality assessment are introduced, among which the Haar wavelet-based perceptual similarity index, known as HaarPSI, provides the best target acquisition prediction results. It is shown that the similarity between the target and the background at the boundary between visually lossless and visually lossy compression does not change significantly compared to the case when an uncompressed image is used. In future work, through subjective tests, it is necessary to check whether this presence of compression at the threshold of just noticeable differences will affect the human target acquisition performance. Similarity values are compared with the results of subjective tests of the well-known target Search_2 database, where the degree of agreement between objective and subjective scores, measured through linear correlation, reached a value of 90%.

Target acquisition performance comparison of active continuous-wave and range-gated imaging systems at 1.6 and 2.1 μm

Target acquisition performance comparison of active continuous-wave and range-gated imaging systems at 1.6 and 2.1 μm

Constant-Modulus Waveform Design for Dual-Function Radar-Communication Systems in the Presence of Clutter

We investigate the constant-modulus (CM) waveform design for dual-function radar communication systems in the presence of clutter. To minimize the interference power and enhance the target acquisition performance, we use the signal-to-interference-plus-noise-ratio as the design metric. In addition, to ensure the quality of the service for each communication user, we enforce a constraint on the synthesis error of every communication signals. An iterative algorithm, which is based on cyclic optimization, Dinkinbach's transform, and alternating direction of method of multipliers, is proposed to tackle the encountered non-convex optimization problem. Simulations illustrate that the CM waveforms synthesized by the proposed algorithm allow to suppress the clutter efficiently and control the synthesis error of communication signals to a low level.

Mere za estimaciju klatera na slici i performanse akvizicije cilja

Introduction/purpose: Measuring target acquisition performance in imaging systems with human-in-the-loop plays an essential role in military applications. This paper presents an extended review on the application of image clutter metrics for target acquisition, with the aim of using objective measures to predict the detection probability, false alarm probability and mean search time of the target in the image. Methods: To determine the degree of clutter, simple features on the global (picture-wise) and local (target-wise) level were used as well as contrast-based clutter metrics, target size and metrics derived from image quality assessment measures. Along with the standard ones, the features derived from the distribution of mean subtracted contrast normalized coefficients were also used. To compare the results of the objective scores and the experimental results obtained on the publicly available Search_2 dataset, regression laws accepted in the literature were applied. Linear correlations and rank correlations were used as quantitative measures of agreement. Results: It is shown that the best agreement with target acquisition indicators is obtained by applying clutter metrics derived from image quality assessment measures. The correlation with the results of subjective tests is up to 90%, which indicates the need for further research. A special contribution of the paper is the analysis of the target acquisition prediction performance using simple features at the global and local level, where it is shown that the prediction performance can be improved by determining the features around the target. Furthermore, it was shown that the false alarm probability and the probability of detection can be predicted based on the mean target search time in the image with a probability higher than 90%. Conclusion: In addition to obtaining a high degree of agreement between the objective metrics of clutter and the results of subjective tests (up to 90%), there is a need to improve the existing and develop new metrics as well as to conduct new subjective tests.

Exploring the mechanisms of target acquisition performance in esports: The role of component kinematic phases on a first person shooter motor skill.

When quantifying elements of performance in bimanual tasks, such as surgery or sports, it is important to understand the errors that participants make to facilitate skill improvement. Esports lags behind when quantifying the motor skills that differentiate elites and amateurs. The purpose of this study was to leverage a large existing kinematic dataset to identify whether previously observed differences in end point performance among gamers of varying expertise, across training days within expertise groups and between stimulation conditions resulted from differences in performance during specific phases of target acquisition movements. Specifically, we evaluated the position and velocity of cursor movements to show for the first time the differences in the component phases of target acquisition movements among first person shooter gamers of various expertise and non-gamers. We also established the dose-response of these components to deliberate practice and the effect of neurostimulation on the improvement of these components in each expertise group. Overall, gamers of higher expertise show evidence of superior motor planning and sensory-motor integration and that these qualities can be improved with training. Future work should more closely examine the sub-movements and classify biomechanical movement strategies of target acquisition skills among gamers.

The Effects of Whole-Body Vibration and Head Supported Mass on Performance and Muscular Demand

For military rotary-wing aircrew, little is known about the interactive effects of vibration exposure and the addition of head supported mass (HSM) on target acquisition performance, head kinematics, and muscular demand. Sixteen healthy male participants wore an aviator helmet with replica night vision goggles and completed rapid aiming head movements to acquire visual targets in axial and off-axis movement trajectories while secured in a Bell-412 helicopter seat mounted to a human-rated shaker platform. HSM configuration (with or without a counterweight (CW)) and vertical whole-body vibration (WBV) conditions (vibration or no vibration exposure) were manipulated as independent variables. WBV exposure degraded target acquisition performance and lengthened time to peak velocity of head movements. For yaw peak velocity in the axial movement trajectory, peak velocity was 9.9%, 11.6%, and 8.4% higher in the noCW + WBV condition compared to the CW + WBV, CW + noWBV, and noCW + noWBV conditions, respectively.

The effect of computer mouse mass on target acquisition performance among action video gamers

Advances in human performance have shifted research attention from individuals towards understanding the effects that equipment can have on their performance. In esports, the effect of gaming peripherals on performance has only recently been explored. In this study, we investigated the effect of computer mouse mass on gaming skill. 72 video game players performed a target acquisition task, a pertinent composite skill in first-person shooter (FPS) video games, while using computer mice that varied only by their mass (50g, 60g, 90g & 100g). Results showed that participants were 4% faster and 9% more accurate with 50g, 60g, and 90g mice compared to the 100g mouse. They were also 34% more accurate and 14% more precise when using lower control-display gain and preferred lighter mice (50g and 60g) when performing the skill at a lower control-display gain. Taken together, using a lighter mouse at lower sensitivity may augment target acquisition performance among video gamers.

Model for selecting the Earth observation satellite systems by object recognition probability

Model for selecting the Earth observation satellite systems by object recognition probability

On Motor Performance in Virtual 3D Object Manipulation.

Fitts's law facilitates approximate comparisons of target acquisition performance across a variety of settings. Conceptually, also the index of difficulty of 3D object manipulation with six degrees of freedom can be computed, which allows the comparison of results from different studies. Prior experiments, however, often revealed much worse performance than one would reasonably expect on this basis. We argue that this discrepancy stems from confounding variables and show how Fitts's law and related research methods can be applied to isolate and identify relevant factors of motor performance in 3D manipulation tasks. The results of a formal user study ( n=21) demonstrate competitive performance in compliance with Fitts's model and provide empirical evidence that simultaneous 3D rotation and translation can be beneficial.

Effects of Resolution, Range, and Image Contrast on Target Acquisition Performance.

We sought to determine the joint influence of resolution, target range, and image contrast on the detection and identification of targets in simulated naturalistic scenes. Resolution requirements for target acquisition have been developed based on threshold values obtained using imaging systems, when target range was fixed, and image characteristics were determined by the system. Subsequent work has examined the influence of factors like target range and image contrast on target acquisition. We varied the resolution and contrast of static images in two experiments. Participants (soldiers) decided whether a human target was located in the scene (detection task) or whether a target was friendly or hostile (identification task). Target range was also varied (50-400 m). In Experiment 1, 30 participants saw color images with a single target exemplar. In Experiment 2, another 30 participants saw monochrome images containing different target exemplars. The effects of target range and image contrast were qualitatively different above and below 6 pixels per meter of target for both tasks in both experiments. Target detection and identification performance were a joint function of image resolution, range, and contrast for both color and monochrome images. The beneficial effects of increasing resolution for target acquisition performance are greater for closer (larger) targets.

On use of image quality metrics for perceptual blur modeling: image/video compression case

Linear system theory is employed to make target acquisition performance predictions for electro-optical/infrared imaging systems where the modulation transfer function (MTF) may be imposed from a nonlinear degradation process. Previous research relying on image quality metrics (IQM) methods, which heuristically estimate perceived MTF has supported that an average perceived MTF can be used to model some types of degradation such as image compression. Here, we discuss the validity of the IQM approach by mathematically analyzing the associated heuristics from the perspective of reliability, robustness, and tractability. Experiments with standard images compressed by x.264 encoding suggest that the compression degradation can be estimated by a perceived MTF within boundaries defined by well-behaved curves with marginal error. Our results confirm that the IQM linearizer methodology provides a credible tool for sensor performance modeling.

A battle tank simulator for eye and hand coordination tasks under horizontal whole-body vibration

This paper describes the development of a simulator to reproduce gunner’s target tracking tasks in a main battle tank, under whole-body vibration conditions. For specifying the vibration and tracking conditions, three-degree-of-freedom acceleration was measured in a tracked armored vehicle, equipped with a 105 mm cannon, running in a battlefield test track. The electrohydraulic dynamics of the turret systems was experimentally identified as black-box autoregressive functions. A pneumatic actuation system and a real-time control software were designed to reproduce horizontal, single-axis periodic motion with the dominant frequency observed in field measurements. The control software displays the target and sight points and acquires the turret pointing command from an adapted gunner’s handle joystick. The root mean square error between target and simulated turret position allows assessing gunner’s target acquisition and tracking performance under periodic vibration.

Performance evaluation of different age groups for gestural interaction: a case study with Microsoft Kinect and Leap Motion

With the thriving of different natural interaction paradigms—such as gesture-based interfaces—it becomes important to understand how these novel interfaces can influence users’ performance when it comes to their age. Recent advances made in human–computer interaction allow us to manipulate digital contents more intuitively; however, no work has yet been reported that systematically evaluates how gestural interfaces may influence the performance of different user groups. Different optical sensors, which allow human body acquisition with reliable accuracy, have been released, and with the appearance of such controllers for gesture recognition, it becomes important to understand if different age-related groups display similar performance levels concerning gestural interaction, or, on the other hand, if specific sensors could induce better results than others when dealing with users of different age brackets. In this article, we compare two gesture-sensing devices (Microsoft Kinect and Leap Motion) using the Fitts’ law model to evaluate target acquisition performance, with relation to three user groups: children, young adults and older adults. This case study involved 60 participants that were asked to perform a simple continuous selection task as quickly and accurately as possible using one of the devices for gestural recognition. Indeed, performance results showed statistically significant differences among the age groups in the selection task accomplished. However, when considering the users’ performance with regard to both input devices compared side by side, there were no significant differences in each group of users. We believe this situation could imply that the device itself might not have influenced the users’ performance, but actually the users’ age might. The participants feedback was interesting on account of their behaviors and preferences: Although there are no significant differences in performance, there could be when it comes to user preference.

Selective visual attention based clutter metric with human visual system adaptability.

Most existing clutter metrics are proposed based on fixed structural features and experienced weight measures. In this paper, we identify the clutter as selective visual attention effects and propose a type of clutter metric. First, adaptive structural features are extracted from the blocks with an edge-structure similarity to the target. Next, the confusing blocks are selected by the similarity threshold based on the attention guidance map. The clutter is estimated by quantifying the effects of confusing blocks on target acquisition performance. The comparative field experiments, with a Search_2 dataset, show that the proposed metric is consistent with the adaptability of the human visual system (HVS) and outperforms other metrics.

Performance characterization of night vision equipment based on the triangle orientation discrimination methodology

Night vision equipment is crucial in order to accomplish supremacy and safety of the troops on the battlefield. Evidently, system integrators, ministry of defenses and end-users need access to reliable quantitative characterization of the expected field performance when using night vision equipment. The image intensifier tube is one of the most important engines driving the performance for night vision equipment. As a major tube manufacturer, Photonis investigates the link between its products physical design parameters and the actual end-user field performance. The developments include (1) an end-to-end performance measurement method and test facility, (2) an image-based night vision simulation, and (3) a range estimation model. The purpose is twofold: (1) being able to support the need of the integrators and end-users and (2) further systematic improvement of night vision equipment design. For the end-to-end test, Photonis and TNO cooperated in the implementation of the triangle orientation discrimination (TOD) test for night vision equipment. This test provides a clear and rigorous ranking of the products with respect to their target acquisition performance level. We present the Photonis night vision test laboratory, provide TOD results for a set of night vision devices, and show range prediction examples.

Examining Dynamic Control-Display Gain Adjustments to Assist Mouse-Based Pointing for Youths with Cerebral Palsy

The aim of this research is to improve mouse-based point-and-click target acquisition by users with cerebral palsy (CP), which is a common physical disorder among new-borns as well as youths and adults. Youths with cerebral palsy encounter difficulties accessing computers due to the spastic hand movement. A total of 46 participants with CP took part in three stages of the point-and-click experiments conducted to understand the following: 1) effect of degree of impairment on cursor control (29 participants); 2) a development of a model of movement time (MT) (the time required to travel from home object to the target object) (11 participants); and 3) testing of an algorithm to simplify these tasks (six participants). The MT showed high variability across different degrees of impairment. Therefore, it was deemed necessary to develop a model that explains the variability in MT which cannot be explained by Fitts???s law which expresses a linear relationship between MT (dependent variable) and index of difficulty (ID) (independent variable). The developed model extends the independent variable to include a system factor, movement amplitude and human factors including erroneous click, number of sub-movements (NS), number of slip-offs (NSO), curvature index (CI), and average speed (AS). This model suggested that the CI had influenced MT variability, so therefore the CI was the basis of an algorithm including dynamic control-display (C-D) gain adjustment. The model imitates the movement described by the initial optimized impulse model; the movement is composed of two phases of sub-movements (rapid primary and slow secondary). First, a rapid primary movement is constructed towards the target. If the movement attains the target, then the task is completed. On the other hand, if the movement lands outside the target, a slower corrective movement is required. This process carries on until the target is attained. The primary goal of the task is to reach the target as fast as possible; thus, in an ideal scenario, the subject should perform a single high-velocity movement towards the target. In an ideal case, the independent variables of the developed model are only movement amplitude and AS. The algorithm aims to enhance the performance of point-and-click tasks by a dynamic adjustment of C-D gain. The algorithm showed better performance in primary submovement compared to default Windows mode (the C-D gain is set as 10) but it negated the performance in secondary sub-movements. A summary of the research contributions includes: 1) an understanding of target acquisition performance depending on degree of impairment; 2) development of software that collects information about point-and-click tasks; 3) development of a non-linear model that explains the high variability of MT during point-and-click computer tasks; and 4) an algorithm that uses dynamic C-D gain adjustments to enhance a primary sub-movement (but still needs altering to enhance secondary sub-movements).

Human vision noise model validation for the U.S. Army sensor performance metric

Image noise originating from a sensor system is often the limiting factor in target acquisition perfor- mance, especially when limited by atmospheric transmission or low-light conditions. To accurately predict target acquisition range performance for a wide variety of imaging systems, image degradation introduced by the sen- sor must be properly combined with the limitations of the human visual system (HVS). This crucial step of incor- porating the HVS has been improved and updated within NVESD's latest imaging system performance model. The new noise model discussed here shows how an imaging system's noise and blur are combined with the contrast threshold function (CTF) to form the system CTF. Model calibration constants were found by presenting low-contrast sine gratings with additive noise in a two alternative forced choice experiment. One of the principal improvements comes from adding an eye photon noise term allowing the noise CTF to be accurate over a wide range of luminance. The latest HVS noise model is then applied to the targeting task performance metric respon- sible for predicting system performance from the system CTF. To validate this model, human target acquisition performance was measured from a series of infrared and visible-band noise-limited imaging systems. © 2014

Effects of perceptual complexity on older and younger adults’ target acquisition performance

The present study evaluated the effects of the three perceptual complexity factors: number of elements, colour variety, and graphical background clutter level, on older and younger adults’ target acquisition time within a computer display. Experiment 1 manipulated the total number of icons, Experiment 2 manipulated the variety of icon colours, and Experiment 3 manipulated the clutter level of the graphical background on the display. In each experiment, 12 older and 12 younger adults were asked to move a cursor to a target icon on the display as quickly and accurately as possible. Target size and distance to the cursor were also manipulated to yield different difficulties of targets. Target acquisition time and Fitts’ law slope were analysed. Results showed that target acquisition time increased for more difficult targets under all the three complexity factors. The amount of increase was more evident for the factors of colour variety and graphical background clutter than for the number of icons. Older participants performed more slowly than younger participants did, particularly for more difficult targets. However, the impact of the three complexity factors on acquisition time appeared to be comparable for both age groups. The results suggest that implementations of colour varieties and graphical backgrounds on interfaces should be restricted, especially when icon acquisition is a common activity involved in interacting with an interface.

Hidden Markov Models for background clutter

The development of a target acquisition performance model for an electro-optical imaging system is seriously affected by the description of the target and background characteristics at present. Based on the Hidden Markov Model (HMM), a different clutter metric is proposed to quantify the influence of background on target detection in this article. It first simulates the process of recording a target in the human brain by optimizing the HMM parameters to represent the target as far as possible. And then the background clutter is defined to be the similarity, estimated by the computed model parameters, between the target and background. Finally, the newly proposed clutter metric is applied to the Search2 database, and the experiment results prove its superiority to other metrics.

Search and detection modeling of military imaging systems

For more than 50 years, the U.S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD) has been studying the science behind the human processes of searching and detecting, and using that knowledge to develop and refine its models for military imaging systems. Modeling how human observers perform military tasks while using imaging systems in the field and linking that model with the physics of the systems has resulted in the comprehensive sensor models we have today. These models are used by the government, military, industry, and academia for sensor development, sensor system acquisition, military tactics development, and war-gaming. From the original hypothesis put forth by John Johnson in 1958, to modeling time-limited search, to modeling the impact of motion on target detection, to modeling target acquisition performance in different spectral bands, the concept of search has a wide-ranging history. Our purpose is to present a snapshot of that history; as such, it will begin with a description of the search-modeling task, followed by a summary of highlights from the early years, and concluding with a discussion of search and detection modeling today and the changing battlefield. Some of the topics to be discussed will be classic search, clutter, computational vision models and the ACQUIRE model with its variants. We do not claim to present a complete history here, but rather a look at some of the work that has been done, and this is meant to be an introduction to an extensive amount of work on a complex topic. That said, it is hoped that this overview of the history of search and detection modeling of military imaging systems pursued by NVESD directly, or in association with other government agencies or contractors, will provide both the novice and experienced search modeler with a useful historical summary and an introduction to current issues and future challenges.