Facial expressions convey a wealth of information about our feelings, personality and mental state. In this thesis we seek efficient ways of representing and analysing facial expressions of varying intensities. Firstly, we analyse state-of-the-art systems by decomposing them into their fundamental components, in an effort to understand what are the useful practices common to successful systems. Secondly, we address the problem of sequence registration, which emerged as an open issue in our analysis. The encoding of the (non-rigid) motions generated by facial expressions is facilitated when the rigid motions caused by irrelevant factors, such as camera movement, are eliminated. We propose a sequence registration framework that is based on pre-trained regressors of Gabor motion energy. Comprehensive experiments show that the proposed method achieves very high registration accuracy even under difficult illumination variations. Finally, we propose an unsupervised representation learning framework for encoding the spatio-temporal evolution of facial expressions. The proposed framework is inspired by the Facial Action Coding System (FACS), which predates computer-based analysis. FACS encodes an expression in terms of localised facial movements and assigns an intensity score for each movement. The framework we propose mimics those two properties of FACS. Specifically, we propose to learn from data a linear transformation that approximates the facial expression variation in a sequence as a weighted sum of localised basis functions, where the weight of each basis function relates to movement intensity. We show that the proposed framework provides a plausible description of facial expressions, and leads to state-of-the-art performance in recognising expressions across intensities; from fully blown expressions to micro-expressions.

La recherche développée dans cette thèse introduit une approche qualitative pour représenter et raisonner à partir d'entités spatiales dans un espace géographique à deux dimensions. Les patrons de mouvements entre entités dynamiques sont catégorisés à partir d'un modèle qualitatif de relations topologiques entre une ligne orientée et une région, et de relations d'orientation entre deux lignes orientées, respectivement. Les mouvements qualitatifs sont dérivés à partir de relations spatio-temporelles qui caractérisent des entités dynamiques conceptualisées comme des points ou des régions dans un espace à deux dimensions. Cette architecture de raisonnement permet de dériver des configurations de mouvements basiques dérivées à partir d'entités statiques et dynamiques. L'approche est complétée par une qualification de ces configurations à partir d'expressions du langage naturel. Les compositions de mouvements sont étudiées tout comme les transitions possibles dans des cas de données incomplètes. Les tables de compositions sont également explorées et permettent d'étendre les possibilités de raisonnement. Le modèle est expérimenté dans le contexte de l'analyse de trajectoires aériennes et maritimes. / The research developed in this thesis introduces a qualitative approach for representing and reasoning on moving entities in a two-dimensional geographical space. Movement patterns of moving entities are categorized based on a series of qualitative spatial models of topological relations between a directed line and a region, and orientation relations between two directed lines, respectively. Qualitative movements are derived from the spatio-temporal relations that characterize moving entities conceptualized as either points or regions in a two-dimensional space. Such a spatio-temporal framework supports the derivation of the basic movement configurations inferred from moving and static entities. The approach is complemented by a tentative qualification of the possible natural language expressions of the primitive movements identified. Complex movements can be represented by a composition of these primitive movements. The notion of conceptual transition that favors the exploration of possible trajectories in the case of incomplete knowledge configurations is introduced and explored.Composition tables are also studied and provide additional reasoning capabilities. The whole approach is applied to the analysis of flight patterns and maritime trajectories.