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Javier Almazán

Researcher at University of Alcalá

Publications -  9
Citations -  806

Javier Almazán is an academic researcher from University of Alcalá. The author has contributed to research in topics: Intelligent transportation system & Image segmentation. The author has an hindex of 8, co-authored 9 publications receiving 685 citations.

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Proceedings ArticleDOI

DriveSafe: An app for alerting inattentive drivers and scoring driving behaviors

TL;DR: DriveSafe is the first app for smartphones based on inbuilt sensors able to detect inattentive behaviors evaluating the quality of the driving at the same time and represents a new disruptive technology because it provides similar ADAS features that found in luxury cars.
Journal ArticleDOI

Assisting the Visually Impaired: Obstacle Detection and Warning System by Acoustic Feedback

TL;DR: The design is completed with acoustic feedback to assist visually impaired users while approaching obstacles and audio bone conducting technology is employed to play these sounds without interrupting the visually impaired user from hearing other important sounds from its local environment.
Proceedings ArticleDOI

On combining visual SLAM and dense scene flow to increase the robustness of localization and mapping in dynamic environments

TL;DR: The combination of visualSLAM and dense scene flow allows to obtain an accurate localization, improving considerably the results of traditional visual SLAM methods and GPS-based approaches.
Journal ArticleDOI

Expert video-surveillance system for real-time detection of suspicious behaviors in shopping malls

TL;DR: A complete expert system focused on the real-time detection of potentially suspicious behaviors in shopping malls and an innovative tracking algorithm based on people trajectories as the most part of state-of-the-art methods, but also on people appearance in occlusion situations are proposed.
Proceedings ArticleDOI

Vision-based drowsiness detector for real driving conditions

TL;DR: This paper presents a non-intrusive approach for drowsiness detection, based on computer vision, installed in a car, which works in a robust and automatic way, without prior calibration.