This paper proposes a complete framework for accurate face localization on video frames. Detection and forward tracking are first combined according to predefined rules to get a first set of face candidates. Backward tracking is then applied to provide another set of possible localizations. Finally a dynamic programming algorithm is used to select the candidates that minimize a specific cost function. This method was designed to handle different scale, pose and lighting conditions. The experiments show that it improves the face detection rate compared to a frame-based detector and provides a higher precision than a forward information-based tracker.
Notas
IFIP International Conference on Artificial Intelligence in Theory and Practice - Machine Vision
Información general
Fecha de exposición:agosto 2006
Fecha de publicación:agosto 2006
Idioma del documento:Inglés
Evento:19 th IFIP World Computer Congress - WCC 2006
Institución de origen:Red de Universidades con Carreras en Informática (RedUNCI)
Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)