29 research outputs found
Precise Non-Intrusive Real-Time Gaze Tracking System for Embedded Setups
This paper describes a non-intrusive real-time gaze detection system, characterized by a precise determination of a subject's pupil centre. A narrow field-of-view camera (NFV), focused on one of the subject's eyes follows the head movements in order to keep the pupil centred in the image. When a tracking error is observed, feedback provided by a second camera, in this case a wide field-of-view (WFV) camera, allows quick recovery of the tracking process. Illumination is provided by four infrared LED blocks synchronised with the electronic shutter of the eye camera. The characteristic shape of corneal glints produced by these illuminators allows optimizing the image processing algorithms for gaze detection developed for this system. The illumination power used in this system has been limited to well below maximum recommended levels. After an initial calibration procedure, the line of gaze is determined starting from the vector defined by the pupil centre and a valid glint. The glints are validated using the iris outline to avoid glint distortion produced by changes in the curvature on the ocular globe. In order to minimize measurement error in the pupil-glint vector, algorithms are proposed to determine the pupil centre at sub-pixel resolution. Although the paper describes a desk-mounted prototype, the final implementation is to be installed on board of a conventional car as an embedded system to determine the line of gaze of the driver
Distributed Real-Time Computation of the Point of Gaze
This paper presents a minimally intrusive real-time gaze-tracking prototype to be used in several scenarios, including a laboratory stall and an in-vehicle system. The system requires specific infrared illumination to allow it to work with variable light conditions. However, it is minimally intrusive due to the use of a carefully configured switched infrared LED array. Although the perceived level of illumination generated by this array is high, it is achieved using low-emission infrared light beams. Accuracy is achieved through a precise estimate of the center of the user's pupil. To overcome inherent time restrictions while using low-cost processors, its main image-processing algorithm has been distributed over four main computing tasks. This structure not only enables good performance, but also simplifies the task of experimenting with alternative computationally-complex algorithms and with alternative tracking models based on locating both user eyes and several cameras to improve user mobility
General tree enumeration.
<p>The tree begins at element 0 and continues enumerating the elements following the red arrows. When a terminal element is reached, the enumeration returns to the immediate previous unfinished branch.</p
Performance of the solvers and processors.
<p>a) The myelinated axon is the ideal scenario to exploit the GPU implementation of <i>Neurite</i>, where the time consumptions is reduced from days to minutes. For the dendritic tree b) and the damaged axon c), the GPU implementation did not show any advantage compared to the CPU implementation.</p
Hodgkin-Huxley parameters.
<p><i>Na</i><sub><i>v</i></sub> and <i>K</i><sub><i>v</i></sub> parameters. Potential and time units are, respectively, <i>mV</i> and <i>ms</i> in this table. Note that </p><p></p><p></p><p></p><p><mi>G</mi><mo>¯</mo></p><p><mi>N</mi><mi>a</mi></p><p></p><p></p><p></p> and <p></p><p></p><p></p><p><mi>G</mi><mo>¯</mo></p><mi>K</mi><p></p><p></p><p></p> are the maximal <i>Na</i><sub><i>v</i></sub> and <i>K</i><sub><i>v</i></sub> conductances, respectively, and are taken from the original HH model [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116532#pone.0116532.ref012" target="_blank">12</a>].<p></p><p>Hodgkin-Huxley parameters.</p
PDE model parameters.
<p><i>d</i> and <i>h</i> are the neurite diameter and membrane thickness respectively; the subscript <i>my</i> indicates that the values are for each one of the <i>n</i><sub><i>my</i></sub> myelin layers.</p><p>PDE model parameters.</p
General discretization framework.
<p>Each element <i>i</i> (and its corresponding <i>mm</i>) is related to its <i>pa</i>, <i>rc</i>, and <i>lc</i> in the case that <i>i</i> is at a branching point (if not, <i>lc</i> does not exist).</p
APs propagation for healthy and damaged axons.
<p>The decrease in the potential corresponds to a mild axial macroscopic strain (25%) at fast axial strain rate (∼ 400 <i>s</i><sup>−1</sup>), see Ref. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116532#pone.0116532.ref011" target="_blank">11</a>] for more details.</p
Time consumptions for the damaged axon.
<p>The total number of elements is 525.</p><p>Time consumptions for the damaged axon.</p
Time consumptions for the myelinated axon.
<p>The total number of elements is 251,894.</p><p>Time consumptions for the myelinated axon.</p