Two channels have been distinguished in human interaction: one transmits explicit
messages, which may be about anything or nothing; the other transmits implicit messages …

Recently, different machine learning methods have been introduced to tackle the
challenging few-shot learning scenario that is, learning from a small labeled dataset related …

A novel learning procedure, called FloatBoost, is proposed for learning a boosted classifier
for achieving the minimum error rate. FloatBoost learning uses a backtrack mechanism after …

A new boosting algorithm, called FloatBoost, is proposed to overcome the monotonicity
problem of the sequential AdaBoost learning. AdaBoost [1, 2] is a sequential forward search …

We present a novel method of nonlinear discriminant analysis involving a set of locally linear
transformations called" Locally Linear Discriminant Analysis"(LLDA). The underlying idea is …

Face recognition is a task that the human vision system seems to perform almost effortlessly,
yet the goal of building computer-based systems with comparable capabilities has proven to …

Detecting faces across multiple views is more challenging than in a fixed view, eg frontal
view, owing to the significant non-linear variation caused by rotation in depth, self-occlusion …

Une des approches dominantes pour la reconnaissance d'objets est basée sur les
caractéristiques locales. La méthode utilise la description locale calculée au voisinage de …

This paper presents a new probabilistic method for detecting and tracking multiple faces in a
video sequence. The proposed method integrates the information of face probabilities …

2. Background Art Face detection systems essentially operate by Scanning an image for
regions having attributes which would indicate that a region contains a person's face. These …