Open Access
Fast and robust ellipse detection algorithm for head-mounted eye tracking systems
(Springer, 2018) Martinikorena Aranburu, Ion; Cabeza Laguna, Rafael; Villanueva Larre, Arantxa; Urtasun, Iñaki; Larumbe Bergera, Andoni; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
In head-mounted eye tracking systems, the correct detection of pupil position is a key factor in estimating gaze direction. However, this is a challenging issue when the videos are recorded in real-world conditions, due to the many sources of noise and artifacts that exist in these scenarios, such as rapid changes in illumination, reflections, occlusions and an elliptical appearance of the pupil. Thus, it is an indispensable prerequisite that a pupil detection algorithm is robust in these challenging conditions. In this work, we present one pupil center detection method based on searching the maximum contribution point to the radial symmetry of the image. Additionally, two different center refinement steps were incorporated with the aim of adapting the algorithm to images with highly elliptical pupil appearances. The performance of the proposed algorithm is evaluated using a dataset consisting of 225,569 head-mounted annotated eye images from publicly available sources. The results are compared with the better algorithm found in the bibliography, with our algorithm being shown as superior.
Open Access
Supervised descent method (SDM) applied to accurate pupil detection in off-the-shelf eye tracking systems
(ACM, 2018) Larumbe Bergera, Andoni; Cabeza Laguna, Rafael; Villanueva Larre, Arantxa; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
The precise detection of pupil/iris center is key to estimate gaze accurately. This fact becomes specially challenging in low cost frameworks in which the algorithms employed for high performance systems fail. In the last years an outstanding effort has been made in order to apply training-based methods to low resolution images. In this paper, Supervised Descent Method (SDM) is applied to GI4E database. The 2D landmarks employed for training are the corners of the eyes and the pupil centers. In order to validate the algorithm proposed, a cross validation procedure is performed. The strategy employed for the training allows us to affirm that our method can potentially outperform the state of the art algorithms applied to the same dataset in terms of 2D accuracy. The promising results encourage to carry on in the study of training-based methods for eye tracking.
Open Access
Introducing I2Head database
(ACM (Association for Computing Machinery), 2018) Martinikorena Aranburu, Ion; Cabeza Laguna, Rafael; Villanueva Larre, Arantxa; Porta Cuéllar, Sonia; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
I2Head database has been created with the aim to become an optimal reference for low cost gaze estimation. It exhibits the following outstanding characteristics: it takes into account key aspects of low resolution eye tracking technology; it combines images of users gazing at different grids of points from alternative positions with registers of user's head position and it provides calibration information of the camera and a simple 3D head model for each user. Hardware used to build the database includes a 6D magnetic sensor and a webcam. A careful calibration method between the sensor and the camera has been developed to guarantee the accuracy of the data. Different sessions have been recorded for each user including not only static head scenarios but also controlled displacements and even free head movements. The database is an outstanding framework to test both gaze estimation algorithms and head pose estimation methods.
Open Access
Evaluation of accurate eye corner detection methods for gaze estimation
(Bern Open Publishing, 2014) Bengoechea Irañeta, José Javier; Cerrolaza Martínez, Juan José; Villanueva Larre, Arantxa; Cabeza Laguna, Rafael; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
Accurate detection of iris center and eye corners appears to be a promising approach for low cost gaze estimation. In this paper we propose novel eye inner corner detection methods. Appearance and feature based segmentation approaches are suggested. All these methods are exhaustively tested on a realistic dataset containing images of subjects gazing at different points on a screen. We have demonstrated that a method based on a neural network presents the best performance even in light changing scenarios. In addition to this method, algorithms based on AAM and Harris corner detector present better accuracies than recent high performance face points tracking methods such as Intraface.
Open Access
Robust and accurate 2D-tracking-based 3D positioning method: application to head pose estimation
(Elsevier, 2019) Ariz Galilea, Mikel; Villanueva Larre, Arantxa; Cabeza Laguna, Rafael; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
Head pose estimation (HPE) is currently a growing research field, mainly because of the proliferation of human–computer interfaces (HCI) in the last decade. It offers a wide variety of applications, including human behavior analysis, driver assistance systems or gaze estimation systems. This article aims to contribute to the development of robust and accurate HPE methods based on 2D tracking of the face, enhancing performance of both 2D point tracking and 3D pose estimation. We start with a baseline method for pose estimation based on POSIT algorithm. A novel weighted variant of POSIT is then proposed, together with a methodology to estimate weights for the 2D–3D point correspondences. Further, outlier detection and correction methods are also proposed in order to enhance both point tracking and pose estimation. With the aim of achieving a wider impact, the problem is addressed using a global approach: all the methods proposed are generalizable to any kind of object for which an approximate 3D model is available. These methods have been evaluated for the specific task of HPE using two different head pose video databases; a recently published one that reflects the expected performance of the system in current technological conditions, and an older one that allows an extensive comparison with state-of-the-art HPE methods. Results show that the proposed enhancements improve the accuracy of both 2D facial point tracking and 3D HPE, with respect to the implemented baseline method, by over 15% in normal tracking conditions and over 30% in noisy tracking conditions. Moreover, the proposed HPE system outperforms the state of the art on the two databases.
Open Access
Attention to online channels across the path to purchase: an eye-tracking study
(Elsevier, 2019) Cortiñas Ugalde, Mónica; Cabeza Laguna, Rafael; Chocarro Eguaras, Raquel; Villanueva Larre, Arantxa; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Enpresen Kudeaketa; Institute for Advanced Research in Business and Economics - INARBE; Ingeniería Eléctrica, Electrónica y de Comunicación; Gestión de Empresas
Currently, consumers display what is known as omnichannel behavior: the combined use of digital and physical channels providing them with multiple points of contact with firms. We combine the stimulus-organism-response (S-O-R) model and visual attention theory to study how customers’ attention to digital channels varies across different purchasing tasks. We use eye-tracking techniques to observe attention in an experimental setting. The experimental design is composed of four purchasing tasks in four different product categories and measures the attention to the website and time spent on each task in addition to several control variables. The results show that shoppers attend to more areas of the website for purposes of website exploration than for performing purchase tasks. The most complex and time-consuming task for shoppers is the assessment of purchase options. The actual purchase and post-purchase tasks require less time and the inspection of fewer areas of interest. Personal involvement also plays a role in determining these patterns by increasing attention to the product area.
Open Access
SeTA: semiautomatic tool for annotation of eye tracking images
(ACM, 2019) Larumbe Bergera, Andoni; Porta Cuéllar, Sonia; Cabeza Laguna, Rafael; Villanueva Larre, Arantxa; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
Availability of large scale tagged datasets is a must in the field of deep learning applied to the eye tracking challenge. In this paper, the potential of Supervised-Descent-Method (SDM) as a semiautomatic labelling tool for eye tracking images is shown. The objective of the paper is to evidence how the human effort needed for manually labelling large eye tracking datasets can be radically reduced by the use of cascaded regressors. Different applications are provided in the fields of high and low resolution systems. An iris/pupil center labelling is shown as example for low resolution images while a pupil contour points detection is demonstrated in high resolution. In both cases manual annotation requirements are drastically reduced.
Open Access
Improved strategies for HPE employing learning-by-synthesis approaches
(IEEE, 2018) Larumbe Bergera, Andoni; Ariz Galilea, Mikel; Bengoechea Irañeta, José Javier; Segura, Rubén; Cabeza Laguna, Rafael; Villanueva Larre, Arantxa; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
The first contribution of this paper is the presentation of a synthetic video database where the groundtruth of 2D facial landmarks and 3D head poses is available to be used for training and evaluating Head Pose Estimation (HPE) methods. The database is publicly available and contains videos of users performing guided and natural movements. The second and main contribution is the submission of a hybrid method for HPE based on Pose from Ortography and Scaling by Iterations (POSIT). The 2D landmark detection is performed using Random Cascaded-Regression Copse (R-CR-C). For the training stage we use, state of the art labeled databases. Learning-by-synthesis approach has been also used to augment the size of the database employing the synthetic database. HPE accuracy is tested by using two literature 3D head models. The tracking method proposed has been compared with state of the art methods using Supervised Descent Regressors (SDR) in terms of accuracy, achieving an improvement of 60%.
Open Access
Optimizing interoperability between video-oculographic and electromyographic systems
(Rehabilitation Research & Development Service, 2011) Navallas Irujo, Javier; Ariz Galilea, Mikel; Villanueva Larre, Arantxa; San Agustín, Javier; Cabeza Laguna, Rafael; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
A new system is presented that enhances the interoperability between a video-oculographic (VOG) system for mouse movement control and an electromyographic (EMG) system for mouse click detection. The proposed VOG-EMG system combines gaze and muscle information to minimize the number of undesired clicks due to involuntary activations and environmental noise. We tested the system with 24 subjects, comparing three different configurations: one in which the VOG and EMG systems worked independently and two in which we used VOG gaze information to improve the EMG click detection. Results show that the number of false-positive click detections can be reduced when VOG and EMG information is combined. In addition, the third configuration, including extra processing, can reduce the activation delay produced because of the combined use of the VOG and EMG systems. The new VOG-EMG system is meant to be used in noisy environments in which the number of false clicks may impeach a reliable human-computer interaction.
Open Access
Image, brand and price info: do they always matter the same?
(Association for Computing Machinery (ACM), 2019) Cortiñas Ugalde, Mónica; Chocarro Eguaras, Raquel; Villanueva Larre, Arantxa; Gestión de Empresas; Ingeniería Eléctrica, Electrónica y de Comunicación; Enpresen Kudeaketa; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
We study attention processes to brand, price and visual information about products in online retailing websites, simultaneously considering the effects of consumers’ goals, purchase category and consumers’ statements. We use an intra-subject experimental design, simulated web stores and a combination of observational eye-tracking data and declarative measures. Image information about the product is the more important stimulus, regardless of the task at hand or the store involved. The roles of brand and price information are dependent on the product category and the purchase task involved. Declarative measures of relative brand importance are found to be positively related with its observed importance.