
Chaabane DjerabaUniversity of Lille Nord de France · Research unit CRIStAL
Chaabane Djeraba
HDR, PhD computer science
About
273
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Introduction
My research is articulated around several research axes that I describe below. They are located in the field of multimedia indexing and computer vision. The application generally targeted is the analysis of human behavior. The human behavior is located in a personal environment (actions, gestures, facial expressions, pose and orientation of the gaze) or a crowd environment (abnormal events, estimation of flows ...).
Skills and Expertise
Publications
Publications (273)
Facial Expression Recognition (FER) is an active research domain that has shown great progress recently, notably thanks to the use of large deep learning models. However, such approaches are particularly energy intensive, which makes their deployment difficult for edge devices. To address this issue, Spiking Neural Networks (SNNs) coupled with even...
This chapter proposes an innovative descriptor called Local Motion Patterns, which allows us to filter and characterize the motion of facial expressions by freeing us from motion discontinuities. It focuses on the specificities of facial motion in order to enhance the characteristics of the movements induced by facial muscles, and to extract the ma...
The first attempts at facial landmark detection can be traced back to the 1990s. Efforts to tackle the problem of facial landmark detection have long focused on still images, and much work has been published. This chapter explores the two main categories of approaches, generative and discriminative, are detailed along with their developments. Gener...
This chapter discusses how affective states are characterized with respect to facial expressions. It presents two major challenges of facial expression analysis, which are to make the analysis invariant to changes in expression intensity and to be robust to changes in pose and large facial movements. The chapter details how facial analysis processe...
Facial analysis is a growing field of research as it concerns many applications such as security, robotics or telecommunications. This chapter discusses in detail the different steps of the facial analysis process. It deals with a synthesis of the different existing facial analysis systems. Face detection in a digital image consists of highlighting...
This chapter describes current possibilities for spatio‐temporal modeling in a broader context. It reviews both hand‐crafted features and deep learning approaches. The chapter introduces solution proposal. It presents experimental protocol, implementation details and results with their analysis. The chapter provides experiments on two datasets, 300...
Landmark detection is a common and often crucial preprocessing step in the context of facial analysis. This chapter focuses on two widely used datasets, 300W for still images and 300VW for videos. Datasets and evaluation metrics are fundamental to train and demonstrate the validity of algorithms. The chapter reviews the major datasets captured unde...
This chapter focuses on the recognition of expressions in the presence of a great diversity of facial movement amplitudes. It explains the different facial regions that characterize macro‐ and micro‐expressions. The chapter identifies the facial regions where it is interesting to extract the coherent motion patterns necessary for an optimal charact...
This chapter explains how the problems of pose variations and large displacements are illustrated through recent learning databases. It reviews the recent facial expression analysis systems used in these databases, with a particular focus on the normalization methods used. The chapter details the innovative acquisition system to simultaneously capt...
Spiking neural networks have shown much promise as an energy-efficient alternative to artificial neural networks. However, understanding the impacts of sensor noises and input encodings on the network activity and performance remains difficult with common neuromorphic vision baselines like classification. Therefore, we propose a spiking neural netw...
Optical flow techniques are becoming increasingly performant and robust when estimating motion in a scene, but their performance has yet to be proven in the area of facial expression recognition. In this work, a variety of optical flow approaches are evaluated across multiple facial expression datasets, so as to provide a consistent performance eva...
Optical flow techniques are becoming increasingly performant and robust when estimating motion in a scene, but their performance has yet to be proven in the area of facial expression recognition. In this work, a variety of optical flow approaches are evaluated across multiple facial expression datasets, so as to provide a consistent performance eva...
This paper presents "Bina-Rep", a simple representation method that converts asynchronous streams of events from event cameras to a sequence of sparse and expressive event frames. By representing multiple binary event images as a single frame of $N$-bit numbers, our method is able to obtain sparser and more expressive event frames thanks to the ret...
In this paper, we introduce a novel approach for face stereo reconstruction in passive stereo vision system. Our approach is based on the generation of a facial disparity map, requiring neither expensive devices nor generic face models. It consists of incorporating face properties in the disparity estimation to enhance the 3D face reconstruction. A...
Video facial expression recognition is useful for many applications and received much interest lately. Although some methods give good results in controlled environments (no occlusion), recognition in the presence of partial facial occlusion remains a challenging task. To handle facial occlusions, methods based on the reconstruction of the occluded...
Although facial landmark localization (FLL) approaches are becoming increasingly accurate in identifying facial components, one question remains unanswered: what is the impact of these approaches on subsequent, related tasks In this paper, we focus on facial expression recognition (FER), where facial landmarks are used for face registration, which...
Although facial landmark localization (FLL) approaches are becoming increasingly accurate in identifying facial components, one question remains unanswered: what is the impact of these approaches on subsequent, related tasks? In this paper, we focus on facial expression recognition (FER), where facial landmarks are used for face registration, which...
This paper overviews two interdependent issues important for mining remote sensing data (e.g. images) obtained from atmospheric monitoring missions. The first issue relates the building new public datasets and benchmarks, which are hot priority of the remote sensing community. The second issue is the investigation of deep learning methodologies for...
Although much progress has been made in the facial expression analysis field, facial occlusions are still challenging. The main innovation brought by this contribution consists in exploiting the specificities of facial movement propagation for recognizing expressions in presence of important occlusions. The movement induced by an expression extends...
Many research works focus on leveraging the complementary geometric information of indoor depth sensors in vision tasks performed by deep convolutional neural networks, notably semantic segmentation. These works deal with a specific vision task known as "RGB-D Indoor Semantic Segmentation". The challenges and resulting solutions of this task differ...
With the advent of neuromorphic hardware, spiking neural networks can be a good energy-efficient alternative to artificial neural networks. However, the use of spiking neural networks to perform computer vision tasks remains limited, mainly focusing on simple tasks such as digit recognition. It remains hard to deal with more complex tasks (e.g. seg...
Video facial expression recognition is useful for many applications and received much interest lately. Although some solutions give really good results in a controlled environment (no occlusion), recognition in the presence of partial facial occlusion remains a challenging task. To handle occlusions, solutions based on the reconstruction of the occ...
In this paper, we develop a new method that recognizes facial expressions, on the basis of an innovative Local Motion Patterns (LMP) feature. The LMP feature analyzes locally the motion distribution in order to separate consistent mouvement patterns from noise. Indeed, facial motion extracted from the face is generally noisy and without specific pr...
Although much progress has been made in the facial expression analysis field, facial occlusions are still challenging. The main innovation brought by this contribution consists in exploiting the specificities of facial movement propagation for recognizing expressions in presence of important occlusions. The movement induced by an expression extends...
Optical flow techniques are becoming increasingly performant and robust when estimating motion in a scene, but their performance has yet to be proven in the area of facial expression recognition. In this work, a variety of optical flow approaches are evaluated across multiple facial expression datasets, so as to provide a consistent performance eva...
Although much progress has been made in the facial expression analysis field, facial occlusions are still challenging. The main innovation brought by this contribution consists in exploiting the specificities of facial movement propagation for recognizing expressions in presence of important occlusions. The movement induced by an expression extends...
Face alignment remains difficult under uncontrolled conditions due to many variations that may considerably impact facial appearance. Recently, video-based approaches have been proposed, which take advantage of temporal coherence to improve robustness. These new approaches suffer from limited temporal connectivity. We show that early, direct pixel...
In uncontrolled settings occlusions occur and interfere with facial expressions recognition task. It is interesting to limit the number of regions required for face expression recognition task in order to moderate the occlusion interference. We propose a weighting scheme that ranks the facial regions needed to recognize expressions. Weights are cal...
In this paper, we develop a new method that recognizes facial expressions, on the basis of an innovative local motion patterns feature, with three main contributions. The first one is the analysis of the face skin temporal elasticity and face deformations during expression. The second one is a unified approach for both macro and micro expression re...
Face alignment is an essential task for many applications. Its objective is to locate feature points on the face, in order to identify its geometric structure. Under unconstrained conditions, the different variations that may occur in the visual context, together with the instability of face detection, make it a difficult problem to solve. While ma...
Recent methodologies for facial expression recognition have been proposed and have obtained good results in near-frontal view. However, these situations do not fairly represent in-the-wild challenges, where expressions are natural and the subject is free of its movement. This is reflected in the accuracy drop of facial expression methods obtained o...
A wide variety of face models have been used in the recognition of full or micro facial expressions in image sequences. However, the existing methods only address one family of expression at a time, as micro-expressions are quite different from full-expressions in terms of facial movement amplitude and/or texture changes. In this paper we address t...
L'importance de la dynamique faciale pour la reconnaissance d'expressions spontanées a été prouvée dans l'iden-tification subtile des déformations physiques du visage. Les approches courantes de reconnaissance d'expressions fa-ciales sont performantes sur des datasets où l'environne-ment est contrôlé et les expressions sont actées. Cepen-dant, ces...
In this paper, we introduce a novel approach for face depth estimation in a passive stereo vision system. Our approach is based on rapid generation of facial disparity maps, requiring neither expensive devices nor generic face models. It consists in incorporating face properties into the disparity estimation process to enhance the 3D face reconstru...
This paper presents a novel descriptor for face depth images, generalizing the well-known Local Binary Pattern (LBP), in order to enhance its discriminative power for smooth depth images. The proposed descriptor is based on detecting shape patterns from face surfaces and enables accurate and fast description of shape variation in depth images. It i...
This paper presents cross-database evaluations of automatic appearance-based gender recognition methodology using normalized raw pixels and SVM classifier under unconstrained settings. Proposed method uses both histogram specification and feature space normalization on automatically aligned faces to achieve reliable recognition rate for real scenar...
Recognizing human facial expression and emotion by computer is an interesting and challenging problem. In this paper, we propose a method for recognizing negative emotions through an appropriate representation of facial features from relevant face regions displayed in video streams and still images. A measure that is sensitive to facial movements i...
This paper addresses the problem of head pose estimation in order to infer non-intrusive feedback from users about gaze attention. The proposed approach exploits the bilateral symmetry of the face. Size and orientation of the symmetrical area of the face is used to estimate roll and yaw poses by the mean of decision tree model. The approach does no...
Combinatorics is the area of mathematics concerned with counting collections of mathematical objects. We begin by discussing several elementary combinatorial issues such as permutations, the power set of a finite sets, the inclusion-exclusion principle, and continue with more involved combinatorial techniques that are relevant for data mining, such...
The existence of directions that are preserved by linear transformations (which are referred to as eigenvectors) has been discovered by L. Euler in his study of movements of rigid bodies. This work was continued by Lagrange, Cauchy, Fourier, and Hermite. The study of eigenvectors and eigenvalues acquired increasing significance through its applicat...
The notion of norm is introduced for evaluating the magnitude of vectors and, in turn, allows the definition of certain metrics on linear spaces equipped with norms.
Clustering and classification, two central data mining activities, require the evaluation of degrees of dissimilarity between data objects.
Convex sets and functions have been studied since the nineteenth century; the twentieth century literature on convexity began with Bonnesen and Fenchel’s book [1], subsequently reprinted as [2].
Graphs model relations between elements of sets. The term “graph” is suggested by the fact that these mathematical structures can be graphically represented.
Linear spaces are among the most important and widely used mathematical structures. Linear spaces consist of elements called vectors.
Topology is an area of mathematics that investigates both the local and the global structure of space
Clustering is the process of grouping together objects that are similar. The groups formed by clustering are referred to as clusters
We introduce the notion of a partially ordered set (poset) we and define several types of special elements associated with partial orders.
The analysis of human affective behavior has attracted increasing attention from researchers in psychology, computer science, neuroscience, and related disciplines. We focus on the recognition of the affect state of a single person from video streams. We create a model that allows to estimate the state of four affective dimensions of a person which...
The study of topological properties of metric spaces allows us to present an introduction to the dimension theory of these spaces, a topic that is relevant for data mining due to its role in understanding the complexity of searching in data sets that have a natural metric structure.
In this chapter, dedicated to set-theoretical bases of data mining, we assume that the reader is familiar with the notion of a set, membership of an element in a set, and elementary set theory. After a brief review of set-theoretical operations we discuss collections of sets, ordered pairs, and set products.
This chapter presents an introduction to the relational model, which is of paramount importance for data mining. We continue with certain equivalence relations (and partitions) that can be associated to sets of attributes of tables.
Subsets of ℝⁿ may have “intrinsic” dimensions that are much lower than n. Consider, for example, two distinct vectors a, b ∈ ℝⁿ and the line L = {a + tb | ∈ ℝ}. Intuitively, L has the intrinsic dimensionality 1; however, L is embedded in ℝⁿ and from this point of view is an n-dimensional object. In this chapter we examine formalisms that lead to th...
Association rules have received lots of attention in data mining due to their many applications in marketing, advertising, inventory control, and many other areas.
Lattices can be defined either as special partially ordered sets or as algebras. In this chapter, we present both definitions and show their equivalence. We study several special classes of lattices: modular and distributive lattices and complete lattices. The last part of the chapter is dedicated to Boolean algebras and Boolean functions.
In this paper we will present an approach based on Time Petri net (TPN) for verifying temporal coherence in a SMIL (Synchronized Multimedia Integration Language) document presentation. In our approach, we can model a SMIL document by TPN model by translation of the SMIL elements and attributes into TPN concepts. Some extension of the TPN model is m...
This paper presents an automatic way to discover pixels in a face image that improves the facial expression recognition results. Main contribution of our study is to provide a practical method to improve classification performance of classifiers by selecting best pixels of interest. Our method exhaustively searches for the best and worst feature wi...
This paper tackles the problem of head pose estimation which has been considered an important research task for decades. The proposed approach selects a set of features from the symmetrical parts of the face. The size of bilateral symmetrical area of the face is a good indicator of the Yaw head pose. We train a Decision Tree model in order to recog...
In this paper, we introduce a novel approach for face stereo reconstruction in passive stereo vision system. Our approach is based on the generation of a facial disparity map, requiring neither expensive devices nor generic face models. It consists of incorporating face properties in the disparity estimation to enhance the 3D face reconstruction. A...
Detection of aberration in video surveillance is an important task for public safety. This paper puts forward a simple but effective framework to detect aberrations in video streams using Entropy, which is estimated on the statistical treatments of the spatiotemporal information of a set of interest points within a region of interest by measuring t...
Résumé Dans cet article, nous présentons une méthode géomé-trique d'estimation de la pose de la tête à partir d'images monoculaires. Nous allons démontrer que la taille des ré-gions symétriques du visage est un bon indicateur du mou-vement Pan de la tête. L'approche proposée ne nécessite pas la détection de points spécifiques sur le visage ce qui l...
Résumé Ce travail propose une méthode pour détecter de manière automatique les régions qui contribuent le plus à une bonne classification des visages par rapport à des expressions prédéfinies : joie, surprise, etc. Notre méthode détermine les régions ayant le plus, (respectivement le moins) de pouvoir discriminant en utilisant un réseau de neurones...
Nous présentons dans cet article une approche pour ré-identifier des personnes, c'est-à-dire établir une correspondance d'identité de toutes les occurrences de personnes, dans les journaux télévisés. Notre approche est basée sur des histogrammes spatio-temporels, qui sont des histogrammes contenant, en plus des données de comptage de pixels dans un...
In this paper, we introduce a novel approach for face stereo reconstruction based on stereo vision. The approach is based on real time generation of facial disparity map, requiring neither expensive devices nor generic face model. An algorithm based on incorporating topological information of the face in the disparity estimation process is proposed...
In this article, we present a person re-identification in news video approach. It consists of matching the identity of all occurences of a person. Our approach is based on space-time histograms, that are histograms containing, in addition to pixel counts in a video, their position in space and time. Space-time histograms allow a higher precision th...
With increasing use of multimedia in various domains, several metadata standards appeared these last decades in order to facilitate the manipulation of multimedia contents. These standards help consumers to search content they desire and to adapt the retrieved content according to consumers' profiles and preferences. However, in order to extract in...
Having effective methods to access the desired images is essential nowadays with the availability of a huge amount of digital images. We propose a higher-level visual representation that enhances the traditional part-based Bag of Visual Words (BOW) representation in two aspects. Firstly, we introduce a new multilayer semantic significance analysis...
With increasing use of multimedia in various domains, several metadata standards appeared these last decades in order to facilitate the manipulation of multimedia contents. These standards help consumers to search content they desire and to adapt the retrieved content according to consumers’ profiles and preferences. However, in order to extract in...
The recent growth of multimedia requires an extensive use of metadata for their management. However, a uniform access to metadata is necessary in order to take advantage of them. In this context, several techniques for achieving metadata interoperability have been developed. Most of these techniques focus on matching schemas defined by using one sc...
The recent growth of multimedia requires an extensive use of metadata for their management. However, a uniform access to metadata is necessary in order to take advantage of them. In this context, several techniques for achieving metadata interoperability have been developed. Most of these techniques focus on matching schemas defined by using one sc...
This paper proposes an approach that uses direction and magnitude models to perform human action recognition from videos captured using monocular cameras. A mixture distribution is computed over the motion orientations and magnitudes of optical flow vectors at each spatial location of the video sequence. This mixture is estimated using an online k-...