Displaying Real-Time Videos in Virtual Reality to Evaluate the Dynamics of Views-Out

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Auditory and visual cues are important sensor inputs for biological and artificial systems. They provide crucial information for navigating environments, recognizing categories, animals and people. How to combine effectively these two sensory channels is still an open issue. As a step towards this goal, this paper presents a comparison between three different multi-modal integration strategies, for audiovisual object category detection. We consider a high-level and a low-level cue integration approach, both

Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of higher flexibility and association of semantics to the model. Ideally, a place recognition algorithm should be robust to dynamic changes and it should perform consistently when recognizing a room (for instance a corridor) in different geographical locations. Also, it should be able to categorize places, a crucial capability for transfer

The problem of generating a virtual view of a scene, i.e. a view from a point where there is not a physical camera to capture the scene, has received recently a lot of attention from the computer vision community. This is probably due to the increase of the computational power of computers, which allows to deal with multiple view systems (systems composed of multiple cameras) efficiently. In this document, an introduction to virtual view generation techniques is presented. In a first part, geometric constra

This paper reports on four experimental studies concerning regard to how people use space so as to solve problems collaboratively in virtual environments. Prior to presenting the results, it summarizes the wide range of literature concerning social uses of spatiality in human interactions. The experiments we conducted revealed that virtual space modifies and improves collaborative processes such as division of labor, grounding, communication, coordination, as well as the performance to the task. It conclude

While feedback of the grasping force is necessary to manipulate objects skillfully, most Virtual Reality systems do not provide such feedback. Grasping an object is often reduced to pushing a button on the interface. This paper presents the design and realization of a haptic forceps for microsurgery training, and its integration on a haptic 6DOF DELTA device. Psychophysical experiments were first conducted to determine the critical factors for the design. The haptic forceps has similar dimensions as a micro

When animals explore an environment, they store useful spatial information in their brains. In subsequent visits, they can recall this information and thus avoid dangerous places or find again a food location. This ability, which may be crucial for the animal's survival, is termed "spatial learning". In the late 1940s, theoretical considerations have led researchers to the conclusion that rats establish a "cognitive map" of their environment. This spatial representation can then be used by the animal in ord

We propose a deep study on tissue modelization and classification techniques on T1-weighted MR images. Six approaches have been taken into account to perform this validation study. We consider first the Finite Gaussian Mixture model (A-FGMM) and a Bayes classification. Second method is the same as A-FGMM but introducing a Hidden Markov Random Field (HMRF) model to encode spatial information and classification is then performed by Maximum a Posteriori (MAP). Third, we study a method that models mixture tissu

Humans have the ability to learn. Having seen an object we can recognise it later. We can do this because our nervous system uses an efficient and robust visual processing and capabilities to learn from sensory input. On the other hand, designing algorithms to learn from visual data is a difficult task. More than fifty years ago, Rosenblatt proposed the perceptron algorithm. The perceptron learns from data examples a linear separation, which categorises the data in two classes. The algorithm served as a sim

In human perception, the availability of context enhances recognition and renders it more robust to noise. Even if not all phonemes in a word (or words in a sentence etc.) are correctly perceived, humans can fill in missing parts with the help of cues from the surrounding speech parts. This was proven in studies on human speech perception where recognition of words in sentences under noise was shown to outperform recognition of words in isolation or, even more drastically, of nonsense syllables under noise.

Rendering and animating in real-time a multitude of articulated characters presents a real challenge, and few hardware systems are up to the task. Up to now, little research has been conducted to tackle the issue of real-time rendering of numerous virtual humans. This paper presents a hardware-independent technique that improves the display rate of animated characters by acting on the sole geometric and rendering information. We first review the acceleration techniques traditionally in use in computer graph

In combination with the rapid technical improvements of computers, building large virtual scenes has become a popular field in computer graphics. Often, within a real reconstructed city, a building that has disappeared, or a virtual town, virtual humans populating these scenes are expected to provide a feeling of real life. Our specific aim is to populate these scenes with virtual humans in order to offer assistance in decision making concerning urban infrastructures. In this view, we have to integrate the

Since their inception, interactive virtual environments have not been able to interpret users' gestures. Researchers have investigated a few tentative solutions, but most of them concern a specific set of body parts like hands, arms, or facial expressions. However, when placing a participant in a virtual world to interact with synthetic inhabitants, it would be more convenient and intuitive to use body-oriented actions. To achieve this, we developed a hierarchical model of human actions based on fine-graine

Displaying Real-Time Videos in Virtual Reality to Evaluate the Dynamics of Views-Out

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Biologically Motivated Audio-Visual Cue Integration for Object

Towards Robust Place Recognition for Robot Localization

Multiple-View Scenes: Reconstruction and Virtual Views

DO PARTNERS CARE ABOUT THEIR MUTUAL LOCATION? Spatial awareness in virtual environments.

Design of a haptic forceps for microsurgery training

A connectionist model of spatial learning in the rat

Validation of Tissue Modelization and Classification Techniques in T1-weighted MR Brain Images

New support vector algorithms for multicategorical data applied to real-time object recognition

Error Correcting Posterior Combination for Robust Multi-Band Speech Recognition

Real-time display of virtual humans: levels of details and impostors

Virtual human life simulation and database: why and how

Interacting with virtual humans through body actions