In this work, we present the problem of automatic appearance-based facial analysis with machine learning techniques and describe common specific subproblems like face detection, facial feature detection and face recognition which are the crucial parts of many applications in the context of indexation, surveillance, access-control or human-computer interaction. To tackle this problem, we particu...

Locating the position of a human face in a photograph is likely to be a very complex task, requiring several image and signal processing techniques. This paper proposes a new approach called polygonal facial projection that is able, by measuring specific distances on the image, to extract relevant features and improve efficiency of neural face identification systems (Rowley, 1999) (Moutinho and...

This paper demonstrates a novel lower dimension multi resolution analysis technique to represent facial images using wavelet transform and decimation, which alleviate heavy computational load, reduce noise, produce a representation in low frequency domain and hence make the facial images less sensitive to facial expressions and small occlusions. All coefficients of wavelet transform do not have...

This paper presents an approach to perform neutral facial image recognition through facial expression image. The differential of this work is the previous images processing. First, the dimension is reduced. Next, the image is sliced into gray levels, from the most significant bits to the less significant bits. Finally, eight parallel hopfield neural networks are applied, one for each gray level...

The science of image processing helps to recognize the human gesture for general life applications. Human gestures can be identified by observing the different movements of eyes, mouth, nose and hands. The face is a rich source of information about human behavior. The proposed method of facial expression recognition system is based on PCA and Neural Networks, to recognize the facial expression ...

This paper provides efficient and robust algorithms for real-time face detection and recognition in complex backgrounds. The algorithms are implemented using a series of signal processing methods including Ada Boost, cascade classifier, Local Binary Pattern (LBP), Haar-like feature, facial image pre-processing and Principal Component Analysis (PCA). The Ada Boost algorithm is implemented in a c...

Extracting and understanding of emotion is of high importance for the interaction among human and machine communication systems. The most expressive way to display the human’s emotion is through facial expression analysis. This paper presents and implements an automatic extraction and recognition method of facial expression and emotion from still image. There are two steps to recognize the faci...

We propose a novel expression transfer method based on an analysis of the frequency of multi-expression facial images. We locate the facial features automatically and describe the shape deformations between a neutral expression and non-neutral expressions. The subtle expression changes are important visual clues to distinguish different expressions. These changes are more salient in the frequen...

Temporal segmentation of facial gestures in spontaneous facial behavior recorded in real-world settings is an important, unsolved, and relatively unexplored problem in facial image analysis. Several issues contribute to the challenge of this task. These include non-frontal pose, moderate to large out-of-plane head motion, large variability in the temporal scale of facial gestures, and the expon...