Bengoechea Irañeta, José JavierCerrolaza Martínez, Juan JoséVillanueva Larre, ArantxaCabeza Laguna, Rafael2020-02-052020-02-0520141995-869210.16910/jemr.7.3.3https://academica-e.unavarra.es/handle/2454/36194Accurate 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.8 p.application/pdfengThis work is licensed under a Creative Commons Attribution 4.0 International License.Eye trackingLow costEye inner cornerinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccess