International audienceA single glance at a face is enough to infer a first impression about someone. With the increasing amount of pictures available, selecting the most suitable picture for a given use is a difficult task. This work focuses on the estimation of the image quality of facial portraits. Some image quality features are extracted such as blur, color representation, illumination and it is shown that concerning facial picture rating, it is better to estimate each feature on the different picture parts (background and foreground). The performance of the proposed image quality estimator is evaluated and compared with a subjective facial picture quality estimation experimen
Automatically assessing photo quality from the perspec-tive of visual aesthetics is of great interes...
International audienceAn automated system that provides feedback about aesthetic quality of facial p...
In this thesis, we present an abstract view of image quality assessment algorithms. Most of the rese...
Face quality assessment algorithms play an important role in improving face recognition accuracy and...
The correctness of the generated face data, which is impacted by a number of variables, significantl...
When a person passes by a surveillance camera a sequence of images is obtained. Most of these images...
In recent years, face recognition has received substantial attentions from both research communit...
In biometric studies, quality evaluation of input data is very important, and has proven to have a d...
Abstract—Automatically assessing photo quality from the per-spective of visual aesthetics is of grea...
Quality scores provide a measure to evaluate the utility of biometric samples for biometric recognit...
This dissertation addresses the problem of capturing spectral images for human portraits and evaluat...
Recent advances in facial recognition technology have achieved outstanding performance, but unconstr...
This study presents a new model of the human image quality assessment process: the aim is to highlig...
This paper studies the assessment of the quality of face images, predicting the utility of face imag...
This study presents a new model of the human image quality assessment process: the aim is to highlig...
Automatically assessing photo quality from the perspec-tive of visual aesthetics is of great interes...
International audienceAn automated system that provides feedback about aesthetic quality of facial p...
In this thesis, we present an abstract view of image quality assessment algorithms. Most of the rese...
Face quality assessment algorithms play an important role in improving face recognition accuracy and...
The correctness of the generated face data, which is impacted by a number of variables, significantl...
When a person passes by a surveillance camera a sequence of images is obtained. Most of these images...
In recent years, face recognition has received substantial attentions from both research communit...
In biometric studies, quality evaluation of input data is very important, and has proven to have a d...
Abstract—Automatically assessing photo quality from the per-spective of visual aesthetics is of grea...
Quality scores provide a measure to evaluate the utility of biometric samples for biometric recognit...
This dissertation addresses the problem of capturing spectral images for human portraits and evaluat...
Recent advances in facial recognition technology have achieved outstanding performance, but unconstr...
This study presents a new model of the human image quality assessment process: the aim is to highlig...
This paper studies the assessment of the quality of face images, predicting the utility of face imag...
This study presents a new model of the human image quality assessment process: the aim is to highlig...
Automatically assessing photo quality from the perspec-tive of visual aesthetics is of great interes...
International audienceAn automated system that provides feedback about aesthetic quality of facial p...
In this thesis, we present an abstract view of image quality assessment algorithms. Most of the rese...