Tutorial Viola-Jones

Este tutorial pretende ser una guía para la elaboración de clasificadores basados en el esquema de Viola-Jones haciando uso de la biblioteca OpenCV

Unidad didáctica "El cartero de Neruda" (Ardiente paciencia) de Antonio Skármeta y la versión cinematográfica "El cartero (y Pablo Neruda)" de Michael Radford

Módulo B del Curso La palabra cinematográfica: Didáctica de las relaciones Literatura y Cine, Curso impartido dentro del Programa de Formación y Perfeccionamiento del Profesorado del Colegio oficial de doctores y licenciados en Filosofía y Letras y en Ciencias de Las Palmas (Islas Canarias). Con Convenio de colaboración con la Consejería de Educación, Universidades, Cultura y Deportes (octubre y diciembre de 2004).

A comparison of face and facial feature detectors based on the viola-jones general object detection framework

[EN]The human face provides useful information during interaction; therefore, any system integrating Vision- BasedHuman Computer Interaction requires fast and reliable face and facial feature detection. Different approaches have focused on this ability but only open source implementations have been extensively used by researchers. A good example is the Viola–Jones object detection framework that particularly in the context of facial processing has been frequently used.

Viola-Jones based detectors: How much affects the training set?

[EN]This paper presents a study on the facial feature detection performance achieved using the Viola-Jones framework. A set of classi- ers using two di erent focuses to gather the training samples is created and tested on four di erent datasets covering a wide range of possibili- ties. The results achieved should serve researchers to choose the classi er that better ts their demands.

Face and eye detection on hard datasets

[EN] This paper analyzes the detection and localization performance of the participating face and eye algorithms compared with the Viola Jones detector and four leading commercial face detectors. Performance is characterized under the different conditions and parameterized by per-image brightness and contrast. In localization accuracy for eyes, the groups/companies focusing on long-range face detection outperform leading commercial applications.