The Effect of Real-time Headbox Adjustments on Data Quality

Following a patent owned by Tobii, the framerate of a CMOS camera can be increased by reducing the size of the recording window so that it fits the eyes with minimum room to spare. The position of the recording window can be dynamically adjusted within the camera sensor area to follow the eyes as the participant moves the head. Since only a portion of the camera sensor data is communicated to the computer and processed, much higher framerates can be achieved with the same CPU and camera.Eye trackers can be expected to present data at a high speed, with good accuracy and precision, small latency and with minimal loss of data while allowing participants to behave as normally as possible. In this study, the effect of headbox adjustments in real-time is investigated with respect to the above-mentioned parameters.It was found that, for the specific camera model and tracking algorithm, one or two headbox adjustments per second, as would normally be the case during recording of human participants, could be tolerated in favour of a higher framerate. The effect of adjustment of the recording window can be reduced by using a larger recording window at the cost of the framerate

Using smooth pursuit calibration for difficult-to-calibrate participants

Although the 45-dots calibration routine of a previous study (Blignaut, 2016) provided very good accuracy, it requires intense mental effort and the routine proved to be unsuccessful for young children who struggle to maintain concentration. The calibration procedures that are normally used for difficult-to-calibrate participants, such as autistic children and infants, do not suffice since they are not accurate enough and the reliability of research results might be jeopardised.Smooth pursuit has been used before for calibration and is applied in this paper as an alternative routine for participants who are difficult to calibrate with conventional routines.  Gaze data is captured at regular intervals and many calibration targets are generated while the eyes are following a moving target. The procedure could take anything between 30 s and 60 s to complete, but since an interesting target and/or a conscious task may be used, participants are assisted to maintain concentration.It was proven that the accuracy that can be attained through calibration with a moving target along an even horizontal path is not significantly worse than the accuracy that can be attained with a standard method of watching dots appearing in random order. The routine was applied successfully for a group of children with ADD, ADHD and learning abilities.This result is important as it provides for easier calibration – especially in the case of participants who struggle to keep their gaze focused and stable on a stationary target for long enough

Idiosyncratic Feature-Based Gaze Mapping

It is argued that polynomial expressions that are normally used for remote, video-based, low cost eye tracking systems, are not always ideal to accommodate individual differences in eye cleft, position of the eye in the socket, corneal bulge, astigmatism, etc. A procedure to identify a set of polynomial expressions that will provide the best possible accuracy for a specific individual is proposed.  It is also proposed that regression coefficients are recalculated in real-time, based on a subset of calibration points in the region of the current gaze and that a real-time correction is applied, based on the offsets from calibration targets that are close to the estimated point of regard.It was found that if no correction is applied, the choice of polynomial is critically important to get an accuracy that is just acceptable.  Previously identified polynomial sets were confirmed to provide good results in the absence of any correction procedure.  By applying real-time correction, the accuracy of any given polynomial improves while the choice of polynomial becomes less critical.  Identification of the best polynomial set per participant and correction technique in combination with the aforementioned correction techniques, lead to an average error of 0.32° (sd = 0.10°) over 134 participant recordings.The proposed improvements could lead to low-cost systems that are accurate and fast enough to do reading research or other studies where high accuracy is expected at framerates in excess of 200 Hz

Mapping the Pupil-Glint Vector to Gaze Coordinates in a Simple Video-Based Eye Tracker

In a video-based eye tracker, the normalized pupil-glint vector changes as the eyes move. Using an appropriate model, the pupil-glint vector can be mapped to gaze coordinates. Using a simple hardware configuration with one camera and one infrared source, several mapping functions – some from literature and some derived here – were compared with one another with respect to the accuracy that could be achieved. The study served to confirm the results of a previous study with another data set and to expand on the possibilities that are considered from the previous study. The data of various participants was examined for trends which led to derivation of a mapping model that proved to be more accurate than all but one model from literature. It was also shown that the best calibration configuration for this hardware setup is one that contains fourteen targets while taking about 20 seconds for the procedure to be completed

Standardised instruments for measuring computer attitude and computer anxiety are not necessarily standardised

Computer attitude and computer anxiety are two determining constructs of success with computer related work. In order to enhance the learning process, improve performance, reduce computer resistance, and ensure job satisfaction computer attitude should be improved and computer anxiety minimised. Several instruments for measuring these constructs are available in the literature but not all of them are necessarily applicable to people with a different mother tongue and educational profile than that of the original survey group. Negatively worded items can specifically be responsible for inconsistent findings. Two standardised instruments from literature were applied to a group of labourers with below-average education and an indigenous African language as mother tongue. It was found that, although an instrument can still appear to be internally consistent, it may have a different factor structure than originally intended by the compilers. Recommendations are made of aspects to keep in mind when instruments for measuring computer attitude and computer anxiety are developed for people with a different profile

Using Eye-Tracking to Assess the Application of Divisibility Rules when Dividing a Multi-Digit Dividend by a Single Digit Divisor

Conference ProceedingsThe Department of Basic Education in South Africa has identified certain problem areas in Mathematics of which the factorisation of numbers was specifically identified as a problem area for Grade 9 learners. The building blocks for factorisation should already have been established in Grades 4, 5 and 6. Knowing the divisibility rules, will assist learners to simplify mathematical calculations such as factorisation of numbers, manipulating fractions and determining if a given number is a prime number. When a learner has to indicate, by only giving the answer, if a dividend is divisible by a certain single digit divisor, the teacher has no insight in the learner’s reasoning. If the answer is correct, the teacher does not know if the learner guessed the answer or applied the divisibility rule correctly or incorrectly. A pre-post experiment design was used to investigate the effect of revision on the difference in gaze behaviour of learners before and after revision of divisibility rules. The gaze behaviour was analysed before they respond to a question on divisibility. It is suggested that if teachers have access to learners’ answers, motivations and gaze behaviour, they can identify if learners (i) guessed the answers, (ii) applied the divisibility rules correctly, (iii) applied the divisibility rules correctly but made mental calculation errors, or (iv) applied the divisibility rules wrongly

A cost function to determine the optimum filter and parameters for stabilizing gaze data

Prior to delivery of data, eye tracker software may apply filtering to correct for noise. Although filtering produces much better precision of data, it may add to the time it takes for the reporting of gaze data to stabilise after a saccade due to the usage of a sliding window. The effect of various filters and parameter settings on accuracy, precision and filter related latency is examined. A cost function can be used to obtain the optimal parameters (filter, length of window, metric and threshold for removal of samples and removal percentage). It was found that for any of the FIR filters, the standard deviation of samples can be used to remove 95% of samples in the window so than an optimum combination of filter related latency and precision can be obtained. It was also confirmed that for unfiltered data, the shape of noise, signified by RMS/STD, is around √2 as expected for white noise, whereas lower RMS/STD values were observed for all filters

The effect of fixational eye movements on fixation identification with a dispersion-based fixation detection algorithm

Gaze data of 31 participants of a memory recall experiment was analyzed and the I-DT dispersion based algorithm of Salvucci and Goldberg (2000) was used to identify fixations. It was found that individuals differ considerably with regard to the stability of eye gaze and that fixational eye movements affect the accuracy of fixation identification and the optimum dispersion threshold. It was also found that fixation radius and the distance between the points in a fixation that are the furthest apart are the most reliable metrics for a dispersion-based fixation identification algorithm. Finally, it is argued that the correct setting of dispersion threshold is of utmost importance, especially if the participants are not homogeneous with regard to gaze stability

Performance of a simple remote video-based eye tracker with GPU acceleration

Eye tracking is a well-established tool that is often utilised in research. There are currently many different types of eye trackers available, but they are either expensive, or provide a relatively low sampling frequency. The eye tracker presented in this paper was developed in an effort to address the lack of low-cost high-speed eye trackers. It utilises the Graphical Processing Unit (GPU) in an attempt to parallelise aspects of the process to localize feature points in eye images to attain higher sampling frequencies. Moreover, the proposed implementation allows for the system to be used on a variety of different GPUs. The developed solution is capable of sampling at frequencies of 200 Hz and higher, while allowing for head movements within an area of 10×6×10 cm and an average accuracy of one degree of visual angle. The entire system can be built for less than 700 euros, and will run on a mid-range laptop