Understanding driver behavior and ethnography surrounding the task of driving are essential in the development of human-centric driver assistance systems.

Laboratory for Intelligent and Safe Automobiles University of California at San Diego

Novel instrumented vehicles are used for conducting experiments, where the rich contextual information about vehicle dynamics, surround and driver state are captured for careful, detailed ethnographic studies, as well as realistic data for developing algorithms to analyze multi sensory signals for active safety.

In this presentation, Prof. Mohan M. Trivedi will provide a systems- oriented framework for developing multimodal sensing, inferencing algorithms and human-vehicle interfaces for safer automobiles.

He will consider three main components of the system, driver, vehicle, and vehicle surround. He will discuss various issues and ideas for developing models for these main components as well as activities associated with the complex task of safe driving.

The presentation will include discussion of novel sensory systems and learning algorithms for capturing not only the dynamic surround information of the vehicle but also the state, intent and activity patterns of drivers.

He will also introduce a new type of visual display called “dynamic active display”. These displays present visual information to the driver where driving view and safety-critical visual icons are presented to the driver in a manner that minimizes deviation of her gaze direction without adding to unnecessary visual clutter.

These contributions support the practical promise of the “human-centric active safety” (HCAS) systems in enhancing the safety, comfort, and convenience.

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In this talk, Marco Gori introduce the notion of developmental agents, that are based on the theory of “learning from constraints” (see e.g. http://videolectures.net/marco_gori/).

Perceptual and logic constraints

It is claimed that in most interesting tasks, learning from constraints naturally leads to “deep architectures”, that emerge when following the developmental principle of focusing attention on “easy constraints”, at each stage. Interestingly, this suggests that stage-based learning, as discussed in developmental psychology, might not be primarily the outcome of biology, but it could be instead the consequence of optimization principles and complexity issues that hold regardless of the “body”.

In the second part of the talk, he gives insights on the adoption of the proposed framework in computer vision. The proposed functional approach leads naturally to develop different notions of features, the lower level of which are somehow related to classical SIFT. It is pointed out that the adoption of information-theoretic principles are at the basis of the feature generation either at low or high level of the vision computer hierarchy. The functions that are developed are inherently independent of roto-translations and do acquire scale invariance by the minimization of an appropriate entropy-based measure, that is also at the basis of the focus of attention.

Finally, he gives an overview of different constraints emerging at different layers of the hierarchy, and claim that the overall system is expected to work in any visual environment by acting continuously, with no separation between learning and scene interpretation.

Computer Vision has graduated from a research tool in early 1960s to a mature discipline today. The developments in cameras, computers and memory have contributed in part to this maturing of computer vision. Namely, there is an explosive growth in the number of cameras in public places, the speed of computers has increased significantly and the price of memory has spectacularly decreased. The word camera may be used in a very broad sense since the imaging modalities range from the usual cameras imaging a visual intensity image to thermal image and laser range image. In addition, several applications of computer vision technology are contributing to the solution of a diverse set of societal problems.

Human activities

At The University of Texas at Austin, we are pursuing a number of projects on human activity understanding and face/emotion recognition. Professor Aggarwal will present his research on modeling and recognition of actions and interactions, and human and object interactions. The
object may be a piece of luggage, a car or an unmovable object like a fence. The applications considered include monitoring of: human activities in public places, identification of abandoned baggage and face and emotion recognition. The issues considered in these problems will illustrate the richness of ideas involved and the difficulties associated with understanding human activities. Application of the above research to monitoring and surveillance will be discussed together with actual examples and their solutions.

Roberto Caldelli will present an application for digital terrestrial television, which allows a user, in possession of the electronic health card (CSE) of the Region of Tuscany, to consult with their Electronic Health Record (ESF) on TV at home. The identity of the user, owner of the CSE, is ensured through a process of client authentication, defined by the Tuscany Region, based on a protocol which provides for asymmetric encryption, HTTPS connection and X509 certificates.

Roberto Caldelli

The application allows to view personal health information in a simple and immediate manner, without the need to provide a smart-card reader and having to install special libraries.

This application is a sample implementation for the supply of value-added services through a strong authentication technique, which can be used in other application scenarios that need to provide, safely, personal information.

The thesis work presented is part of a larger project named Autistic Behavior & Computer-based Didactic & Software (ABCDSW).

The mission of the project is the definition of an educational methodology (according to the model Applied Behavior Analysis – ABA), and the development of open source software tools to enhance and improve, in terms of effectiveness and efficiency, the learning process for children with Autism Spectrum Disorder (ASD) also through sharing of knowledge.

Fabio Ceccarelli

The need for unconventional learning programs for children with these syndromes coupled to the attraction that most of them have in the technology (mobile phones, computers and other electronic devices) has led to consider the use of computers as means to enhance learning. Starting from this idea, and using a multidisciplinary team, have been defined the main objectives to be achieved:

• definition (and development) of a specific educational methodology to be effective and efficient for children with ASD;
• creation of ad hoc educational software modules for children affected by autism, in the range of 2-6 years;
• development of tools to monitor the level of learning of children during therapy with educators / parents.