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C. Cacou

Bio: C. Cacou is an academic researcher. The author has an hindex of 1, co-authored 1 publications receiving 700 citations.

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Proceedings ArticleDOI
01 Jul 1999
TL;DR: A new technique for modeling textured 3D faces by transforming the shape and texture of the examples into a vector space representation, which regulates the naturalness of modeled faces avoiding faces with an “unlikely” appearance.
Abstract: In this paper, a new technique for modeling textured 3D faces is introduced. 3D faces can either be generated automatically from one or more photographs, or modeled directly through an intuitive user interface. Users are assisted in two key problems of computer aided face modeling. First, new face images or new 3D face models can be registered automatically by computing dense one-to-one correspondence to an internal face model. Second, the approach regulates the naturalness of modeled faces avoiding faces with an “unlikely” appearance. Starting from an example set of 3D face models, we derive a morphable face model by transforming the shape and texture of the examples into a vector space representation. New faces and expressions can be modeled by forming linear combinations of the prototypes. Shape and texture constraints derived from the statistics of our example faces are used to guide manual modeling or automated matching algorithms. We show 3D face reconstructions from single images and their applications for photo-realistic image manipulations. We also demonstrate face manipulations according to complex parameters such as gender, fullness of a face or its distinctiveness.

4,514 citations

Journal ArticleDOI
TL;DR: This survey focuses on recognition performed by matching models of the three-dimensional shape of the face, either alone or in combination with matching corresponding two-dimensional intensity images.

1,069 citations

Journal ArticleDOI
TL;DR: A deep learning solution to age estimation from a single face image without the use of facial landmarks is proposed and the IMDB-WIKI dataset is introduced, the largest public dataset of face images with age and gender labels.
Abstract: In this paper we propose a deep learning solution to age estimation from a single face image without the use of facial landmarks and introduce the IMDB-WIKI dataset, the largest public dataset of face images with age and gender labels. If the real age estimation research spans over decades, the study of apparent age estimation or the age as perceived by other humans from a face image is a recent endeavor. We tackle both tasks with our convolutional neural networks (CNNs) of VGG-16 architecture which are pre-trained on ImageNet for image classification. We pose the age estimation problem as a deep classification problem followed by a softmax expected value refinement. The key factors of our solution are: deep learned models from large data, robust face alignment, and expected value formulation for age regression. We validate our methods on standard benchmarks and achieve state-of-the-art results for both real and apparent age estimation.

755 citations

Journal ArticleDOI
TL;DR: The complete state-of-the-art techniques in the face image-based age synthesis and estimation topics are surveyed, including existing models, popular algorithms, system performances, technical difficulties, popular face aging databases, evaluation protocols, and promising future directions are provided.
Abstract: Human age, as an important personal trait, can be directly inferred by distinct patterns emerging from the facial appearance. Derived from rapid advances in computer graphics and machine vision, computer-based age synthesis and estimation via faces have become particularly prevalent topics recently because of their explosively emerging real-world applications, such as forensic art, electronic customer relationship management, security control and surveillance monitoring, biometrics, entertainment, and cosmetology. Age synthesis is defined to rerender a face image aesthetically with natural aging and rejuvenating effects on the individual face. Age estimation is defined to label a face image automatically with the exact age (year) or the age group (year range) of the individual face. Because of their particularity and complexity, both problems are attractive yet challenging to computer-based application system designers. Large efforts from both academia and industry have been devoted in the last a few decades. In this paper, we survey the complete state-of-the-art techniques in the face image-based age synthesis and estimation topics. Existing models, popular algorithms, system performances, technical difficulties, popular face aging databases, evaluation protocols, and promising future directions are also provided with systematic discussions.

743 citations

Journal ArticleDOI
TL;DR: The present study, conducted by investigators working separately across the world and with small samples of the population, is clearly preliminary in nature and extent and may fulfill its mission if medical and anthropological investigators continue the work of establishing normative data of the face.
Abstract: When anthropometric methods were introduced into clinical practice to quantify changes in the craniofacial framework, features distinguishing various races/ethnic groups were discovered. To treat congenital or post-traumatic facial disfigurements in members of these groups successfully, surgeons require access to craniofacial databases based on accurate anthropometric measurements. Normative data of facial measurements are indispensable to precise determination of the degree of deviations from the normal. The set of anthropometric measurements of the face in the population studied was gathered by an international team of scientists. Investigators in the country of the given ethnic group, experienced and/or specially trained in anthropometric methods, carried out the measurements. The normal range in each resultant database was then established, providing valuable information about major facial characteristics. Comparison of the ethnic groups' databases with the established norms of the North America whites (NAW) offered the most suitable way to select a method for successful treatment. The study group consisted of 1470 healthy subjects (18 to 30 years), 750 males and 720 females. The largest group (780 subjects, 53.1%) came from Europe, all of them Caucasians. Three were drawn from the Middle-East (180 subjects, 12.2%), five from Asia (300 subjects, 20.4%) and four from peoples of African origin (210 subjects, 14.3%). Their morphological characteristics were determined by 14 anthropometric measurements, 10 of them used already by classic facial artists, Leonardo da Vinci and Albrecht Durer, complemented by four measurements from the nasal, labio-oral and ear regions. In the regions with single measurements, identical values to NAW in forehead height, mouth width, and ear height were found in 99.7% in both sexes, while in those with multiple measurements, vertical measurements revealed a higher frequency of identical values than horizontal ones. The orbital regions exhibited the greatest variations in identical and contrasting measurements in comparison to NAW. Nose heights and widths contrasted sharply: in relation to NAW the nose was very or extremely significantly wide in both sexes of Asian and Black ethnic groups. Among Caucasians, nose height significantly differed from NAW in three ethnic groups, with one shorter and two greater. In the Middle Eastern groups nose width was identical to those of NAW but the height was significantly greater. The present study, conducted by investigators working separately across the world and with small samples of the population, is clearly preliminary in nature and extent. Yet it may fulfill its mission if medical and anthropological investigators continue the work of establishing normative data of the face. These data are urgently needed by medical professionals but have been lacking up till now in western and northern Europe, Asia, and Africa.

649 citations