A morphological approach for segmentation and tracking of human faces

A new technique for segmenting and tracking human faces in video sequences is presented. The technique relies on morphological tools such as using connected operators to extract the connected component that more likely belongs to a face, and partition projection to track this component through the sequence. A binary partition tree (BPT) is used to implement the connected operator. The BPT is constructed based on the chrominance criteria and its nodes are analyzed so that the selected node maximizes an estimation of the likelihood of being part of a face. The tracking is performed using a partition projection approach. Images are divided into face and non-face parts, which are tracked through the sequence. The technique has been successfully assessed using several test sequences from the MPEG-4 (raw format) and the MPEG-7 databases (MPEG-1 format).Peer ReviewedPostprint (published version

Fuzzy-based Propagation of Prior Knowledge to Improve Large-Scale Image Analysis Pipelines

Many automatically analyzable scientific questions are well-posed and offer a variety of information about the expected outcome a priori. Although often being neglected, this prior knowledge can be systematically exploited to make automated analysis operations sensitive to a desired phenomenon or to evaluate extracted content with respect to this prior knowledge. For instance, the performance of processing operators can be greatly enhanced by a more focused detection strategy and the direct information about the ambiguity inherent in the extracted data. We present a new concept for the estimation and propagation of uncertainty involved in image analysis operators. This allows using simple processing operators that are suitable for analyzing large-scale 3D+t microscopy images without compromising the result quality. On the foundation of fuzzy set theory, we transform available prior knowledge into a mathematical representation and extensively use it enhance the result quality of various processing operators. All presented concepts are illustrated on a typical bioimage analysis pipeline comprised of seed point detection, segmentation, multiview fusion and tracking. Furthermore, the functionality of the proposed approach is validated on a comprehensive simulated 3D+t benchmark data set that mimics embryonic development and on large-scale light-sheet microscopy data of a zebrafish embryo. The general concept introduced in this contribution represents a new approach to efficiently exploit prior knowledge to improve the result quality of image analysis pipelines. Especially, the automated analysis of terabyte-scale microscopy data will benefit from sophisticated and efficient algorithms that enable a quantitative and fast readout. The generality of the concept, however, makes it also applicable to practically any other field with processing strategies that are arranged as linear pipelines.Comment: 39 pages, 12 figure

Allowing content-based functionalities in segmentation-based coding schemes

This paper deals with the use of the segmentation tools and principles presented in [10] and [13] for allowing content-based functionalities. In this framework, means for supervised selection of objects in the scene are proposed. In addition, a technique for object tracking in the context of segmentation-based video coding is presented. The technique is independent of the type of segmentation approach used in the coding scheme. The algorithm relies on a double partition of the image that yields spatially homogeneous regions. This double partition permits to obtain the position and shape of the previous object in the current image while computing the projected partition. In order to demonstrate the potentialities of this algorithm, it is applied in a specific coding scheme so that content-based functionalities, such as selective coding, are allowed.Peer ReviewedPostprint (published version

Region-based representations of image and video: segmentation tools for multimedia services

This paper discusses region-based representations of image and video that are useful for multimedia services such as those supported by the MPEG-4 and MPEG-7 standards. Classical tools related to the generation of the region-based representations are discussed. After a description of the main processing steps and the corresponding choices in terms of feature spaces, decision spaces, and decision algorithms, the state of the art in segmentation is reviewed. Mainly tools useful in the context of the MPEG-4 and MPEG-7 standards are discussed. The review is structured around the strategies used by the algorithms (transition based or homogeneity based) and the decision spaces (spatial, spatio-temporal, and temporal). The second part of this paper proposes a partition tree representation of images and introduces a processing strategy that involves a similarity estimation step followed by a partition creation step. This strategy tries to find a compromise between what can be done in a systematic and universal way and what has to be application dependent. It is shown in particular how a single partition tree created with an extremely simple similarity feature can support a large number of segmentation applications: spatial segmentation, motion estimation, region-based coding, semantic object extraction, and region-based retrieval.Peer ReviewedPostprint (published version

Segmentation-based video coding system allowing the manipulation of objects

This paper presents a generic video coding algorithm allowing the content-based manipulation of objects. This manipulation is possible thanks to the definition of a spatiotemporal segmentation of the sequences. The coding strategy relies on a joint optimization in the rate-distortion sense of the partition definition and of the coding techniques to be used within each region. This optimization creates the link between the analysis and synthesis parts of the coder. The analysis defines the time evolution of the partition, as well as the elimination or the appearance of regions that are homogeneous either spatially or in motion. The coding of the texture as well as of the partition relies on region-based motion compensation techniques. The algorithm offers a good compromise between the ability to track and manipulate objects and the coding efficiency.Peer ReviewedPostprint (published version

Image sequence analysis and merging

Peer ReviewedPostprint (published version

Semi-automatic video object segmentation for multimedia applications

A semi-automatic video object segmentation tool is presented for segmenting both still pictures and image sequences. The approach comprises both automatic segmentation algorithms and manual user interaction. The still image segmentation component is comprised of a conventional spatial segmentation algorithm (Recursive Shortest Spanning Tree (RSST)), a hierarchical segmentation representation method (Binary Partition Tree (BPT)), and user interaction. An initial segmentation partition of homogeneous regions is created using RSST. The BPT technique is then used to merge these regions and hierarchically represent the segmentation in a binary tree. The semantic objects are then manually built by selectively clicking on image regions. A video object-tracking component enables image sequence segmentation, and this subsystem is based on motion estimation, spatial segmentation, object projection, region classification, and user interaction. The motion between the previous frame and the current frame is estimated, and the previous object is then projected onto the current partition. A region classification technique is used to determine which regions in the current partition belong to the projected object. User interaction is allowed for object re-initialisation when the segmentation results become inaccurate. The combination of all these components enables offline video sequence segmentation. The results presented on standard test sequences illustrate the potential use of this system for object-based coding and representation of multimedia

Segmentation-based mesh design for motion estimation

Dans la plupart des codec vidéo standard, l'estimation des mouvements entre deux images se fait généralement par l'algorithme de concordance des blocs ou encore BMA pour « Block Matching Algorithm ». BMA permet de représenter l'évolution du contenu des images en décomposant normalement une image par blocs 2D en mouvement translationnel. Cette technique de prédiction conduit habituellement à de sévères distorsions de 1'artefact de bloc lorsque Ie mouvement est important. De plus, la décomposition systématique en blocs réguliers ne dent pas compte nullement du contenu de l'image. Certains paramètres associes aux blocs, mais inutiles, doivent être transmis; ce qui résulte d'une augmentation de débit de transmission. Pour paillier a ces défauts de BMA, on considère les deux objectifs importants dans Ie codage vidéo, qui sont de recevoir une bonne qualité d'une part et de réduire la transmission a très bas débit d'autre part. Dans Ie but de combiner les deux exigences quasi contradictoires, il est nécessaire d'utiliser une technique de compensation de mouvement qui donne, comme transformation, de bonnes caractéristiques subjectives et requiert uniquement, pour la transmission, l'information de mouvement. Ce mémoire propose une technique de compensation de mouvement en concevant des mailles 2D triangulaires a partir d'une segmentation de l'image. La décomposition des mailles est construite a partir des nœuds repartis irrégulièrement Ie long des contours dans l'image. La décomposition résultant est ainsi basée sur Ie contenu de l'image. De plus, étant donné la même méthode de sélection des nœuds appliquée à l'encodage et au décodage, la seule information requise est leurs vecteurs de mouvement et un très bas débit de transmission peut ainsi être réalise. Notre approche, comparée avec BMA, améliore à la fois la qualité subjective et objective avec beaucoup moins d'informations de mouvement. Dans la premier chapitre, une introduction au projet sera présentée. Dans Ie deuxième chapitre, on analysera quelques techniques de compression dans les codec standard et, surtout, la populaire BMA et ses défauts. Dans Ie troisième chapitre, notre algorithme propose et appelé la conception active des mailles a base de segmentation, sera discute en détail. Ensuite, les estimation et compensation de mouvement seront décrites dans Ie chapitre 4. Finalement, au chapitre 5, les résultats de simulation et la conclusion seront présentés.Abstract: In most video compression standards today, the generally accepted method for temporal prediction is motion compensation using block matching algorithm (BMA). BMA represents the scene content evolution with 2-D rigid translational moving blocks. This kind of predictive scheme usually leads to distortions such as block artefacts especially when the motion is important. The two most important aims in video coding are to receive a good quality on one hand and a low bit-rate on the other. This thesis proposes a motion compensation scheme using segmentation-based 2-D triangular mesh design method. The mesh is constructed by irregularly spread nodal points selected along image contour. Based on this, the generated mesh is, to a great extent, image content based. Moreover, the nodes are selected with the same method on the encoder and decoder sides, so that the only information that has to be transmitted are their motion vectors, and thus very low bit-rate can be achieved. Compared with BMA, our approach could improve subjective and objective quality with much less motion information."--Résumé abrégé par UM