8 research outputs found
Robust density modelling using the student's t-distribution for human action recognition
The extraction of human features from videos is often inaccurate and prone to outliers. Such outliers can severely affect density modelling when the Gaussian distribution is used as the model since it is highly sensitive to outliers. The Gaussian distribution is also often used as base component of graphical models for recognising human actions in the videos (hidden Markov model and others) and the presence of outliers can significantly affect the recognition accuracy. In contrast, the Student's t-distribution is more robust to outliers and can be exploited to improve the recognition rate in the presence of abnormal data. In this paper, we present an HMM which uses mixtures of t-distributions as observation probabilities and show how experiments over two well-known datasets (Weizmann, MuHAVi) reported a remarkable improvement in classification accuracy. © 2011 IEEE
Recent Progress in Image Deblurring
This paper comprehensively reviews the recent development of image
deblurring, including non-blind/blind, spatially invariant/variant deblurring
techniques. Indeed, these techniques share the same objective of inferring a
latent sharp image from one or several corresponding blurry images, while the
blind deblurring techniques are also required to derive an accurate blur
kernel. Considering the critical role of image restoration in modern imaging
systems to provide high-quality images under complex environments such as
motion, undesirable lighting conditions, and imperfect system components, image
deblurring has attracted growing attention in recent years. From the viewpoint
of how to handle the ill-posedness which is a crucial issue in deblurring
tasks, existing methods can be grouped into five categories: Bayesian inference
framework, variational methods, sparse representation-based methods,
homography-based modeling, and region-based methods. In spite of achieving a
certain level of development, image deblurring, especially the blind case, is
limited in its success by complex application conditions which make the blur
kernel hard to obtain and be spatially variant. We provide a holistic
understanding and deep insight into image deblurring in this review. An
analysis of the empirical evidence for representative methods, practical
issues, as well as a discussion of promising future directions are also
presented.Comment: 53 pages, 17 figure
Cartographie dense basée sur une représentation compacte RGB-D dédiée à la navigation autonome
Our aim is concentrated around building ego-centric topometric maps represented as a graph of keyframe nodes which can be efficiently used by autonomous agents. The keyframe nodes which combines a spherical image and a depth map (augmented visual sphere) synthesises information collected in a local area of space by an embedded acquisition system. The representation of the global environment consists of a collection of augmented visual spheres that provide the necessary coverage of an operational area. A "pose" graph that links these spheres together in six degrees of freedom, also defines the domain potentially exploitable for navigation tasks in real time. As part of this research, an approach to map-based representation has been proposed by considering the following issues : how to robustly apply visual odometry by making the most of both photometric and ; geometric information available from our augmented spherical database ; how to determine the quantity and optimal placement of these augmented spheres to cover an environment completely ; how tomodel sensor uncertainties and update the dense infomation of the augmented spheres ; how to compactly represent the information contained in the augmented sphere to ensure robustness, accuracy and stability along an explored trajectory by making use of saliency maps.Dans ce travail, nous proposons une représentation efficace de l’environnement adaptée à la problématique de la navigation autonome. Cette représentation topométrique est constituée d’un graphe de sphères de vision augmentées d’informations de profondeur. Localement la sphère de vision augmentée constitue une représentation égocentrée complète de l’environnement proche. Le graphe de sphères permet de couvrir un environnement de grande taille et d’en assurer la représentation. Les "poses" à 6 degrés de liberté calculées entre sphères sont facilement exploitables par des tâches de navigation en temps réel. Dans cette thèse, les problématiques suivantes ont été considérées : Comment intégrer des informations géométriques et photométriques dans une approche d’odométrie visuelle robuste ; comment déterminer le nombre et le placement des sphères augmentées pour représenter un environnement de façon complète ; comment modéliser les incertitudes pour fusionner les observations dans le but d’augmenter la précision de la représentation ; comment utiliser des cartes de saillances pour augmenter la précision et la stabilité du processus d’odométrie visuelle
Recent Progress in Image Deblurring
This paper comprehensively reviews the recent development of image deblurring, including non-blind/blind, spatially invariant/variant deblurring techniques. Indeed, these techniques share the same objective of inferring a latent sharp image from one or several corresponding blurry images, while the blind deblurring techniques are also required to derive an accurate blur kernel. Considering the critical role of image restoration in modern imaging systems to provide high-quality images under complex environments such as motion, undesirable lighting conditions, and imperfect system components, image deblurring has attracted growing attention in recent years. From the viewpoint of how to handle the ill-posedness which is a crucial issue in deblurring tasks, existing methods can be grouped into five categories: Bayesian inference framework, variational methods, sparse representation-based methods, homography-based modeling, and region-based methods. In spite of achieving a certain level of development, image deblurring, especially the blind case, is limited in its success by complex application conditions which make the blur kernel hard to obtain and be spatially variant. We provide a holistic understanding and deep insight into image deblurring in this review. An analysis of the empirical evidence for representative methods, practical issues, as well as a discussion of promising future directions are also presented
Measuring and simulating haemodynamics due to geometric changes in facial expression
The human brain has evolved to be very adept at recognising imperfections in human skin. In particular, observing someone’s facial skin appearance is important in recognising when someone is ill, or when finding a suitable mate. It is therefore a key goal of computer graphics research to produce highly realistic renderings of skin. However, the optical processes that give rise to skin appearance are complex and subtle. To address this, computer graphics research has incorporated more and more sophisticated models of skin reflectance. These models are generally based on static concentrations of skin chromophores; melanin and haemoglobin. However, haemoglobin concentrations are far from static, as blood flow is directly caused by both changes in facial expression and emotional state. In this thesis, we explore how blood flow changes as a consequence of changing facial expression with the aim of producing more accurate models of skin appearance. To build an accurate model of blood flow, we base it on real-world measurements of blood concentrations over time. We describe, in detail, the steps required to obtain blood concentrations from photographs of a subject. These steps are then used to measure blood concentration maps for a series of expressions that define a wide gamut of human expression. From this, we define a blending algorithm that allows us to interpolate these maps to generate concentrations for other expressions. This technique, however, requires specialist equipment to capture the maps in the first place. We try to rectify this problem by investigating a direct link between changes in facial geometry and haemoglobin concentrations. This requires building a unique capture device that captures both simultaneously. Our analysis hints a direct linear connection between the two, paving the way for further investigatio
8th. International congress on archaeology computer graphica. Cultural heritage and innovation
El lema del Congreso es: 'DocumentaciĂłn 3D avanzada, modelado y reconstrucciĂłn de objetos patrimoniales, monumentos y sitios.Invitamos a investigadores, profesores, arqueĂłlogos, arquitectos, ingenieros, historiadores de arte... que se ocupan del patrimonio cultural desde la arqueologĂa, la informática gráfica y la geomática, a compartir conocimientos y experiencias en el campo de la ArqueologĂa Virtual. La participaciĂłn de investigadores y empresas de prestigio será muy apreciada. Se ha preparado un atractivo e interesante programa para participantes y visitantes.Lerma GarcĂa, JL. (2016). 8th. International congress on archaeology computer graphica. Cultural heritage and innovation. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/73708EDITORIA