Giovanni Attolico

A haptic/acoustic application to allow blind the access to spatial information

This paper describes a multi-modal application, based on haptic/acoustic interaction, to allow visually impaired people to access media with high spatial information content, extending the visual and auditory-verbal data with the tactile sensory channel. Haptic interfaces are exploited to enable the use of touch on 3D virtual objects which have a larger and greater flexibility with respect to physical artefacts. The system allows to interact with haptic/acoustic active objects and to select the information that must be shown on the basis of the user requirements. Two different tests, involving the exploration of indoor environment and of complex geographical areas, are presented. Several experiments, with users with different stories and different level of visual disability, have been done. They showed that the haptic/acoustic interaction and the modularity in the information representation help blind people to cope with the serious and challenging task of managing spatial data

Detection of objects carried by people

Our application context is the visual surveillance of archeological sites. In this context the main aim is to detect the presence of people and to scan them in order to recognize intruders on the basis of their gestures. Since an intruder needs some utensils indispensable to perform the illegal actions of excavating on the ancient ruins, intruder detection involves first of all to ascertain if a person is carrying some objects and then recognizing the kind. In this paper we concentrate on the recognition of the objects carried by the detected moving persons. An example-based learning technique is used to first detect people and successively to scan them to recognize the possible carried objects. The patterns to be analysed are represented through the approximation coefficients of their three level wavelet decomposition. Pattern classification is performed through a supervised three layer neural network.

Posture estimation in visual surveillance of archaeological sites

The paper presents a fast and reliable approach to estimate body postures in outdoor visual surveillance. It works on patches corresponding to people, recognized by two subsystems (motion detection and object recognition) on image sequences coming from a still camera. The proposed algorithm is based on an unsupervised clustering approach and is substantially independent from a-priori assumption about the possible output postures. Horizontal and vertical histograms of the binary shapes associated to humans are selected as features. The Manhattan distance is used for building clusters and for run-time classification. After experimental tests the BCLS (Basic Competitive Learning Scheme) algorithm has been selected for the construction of clusters. The whole approach has been verified on real sequences acquired while typical illegal activities involved in stealing were simulated in an archeological site.

Non-destructive evaluation of quality and ammonia content in whole and fresh-cut lettuce by computer vision system

The paper describes the developed hardware and software components of a computer vision system that extracts colour parameters from calibrated colour images and identifies non-destructively the different quality levels exhibited by lettuce (either whole or fresh-cut) during storage. Several colour parameters extracted by computer vision system have been evaluated to characterize the product quality levels. Among these, brown on total and brown on white proved to achieve a good identification of the different quality levels on whole and fresh-cut lettuce (P-value<0.0001). In particular, these two parameters were able to discriminate three levels: very good or good products (quality levels from 5 to 4), samples at the limit of marketability (quality level of 3) and waste items (quality levels from 2 to 1). Quality levels were also chemically and physically characterized. Among the parameters analysed, ammonia content proved to discriminate the marketable samples from the waste in both products typologies (either fresh-cut or whole); even the two classes of waste were well discriminated by ammonia content (P-value<0.0001). A function that infers quality levels from the extracted colour parameters has been identified using a multi-regression model (R2=0.77). Multi-regression also identified a function that predicts the level of ammonia (an indicator of senescence) in the iceberg lettuce from a colour parameter provided by the computer vision system (R2=0.73), allowing a non-destructive evaluation of a chemical parameter that is particularly useful for the objective assessment of lettuce quality. The developed computer vision system offers flexible and simple non-destructive tool that can be employed in the food processing industry to monitor the quality and shelf life of whole and fresh-cut lettuce in a reliable, objective and quantitative way.

People detection in dynamic images

The main aim of this work is people detection in outdoor environments in the context of video surveillance for intruder detection in archeological sites. Our goal is to propose an example-based learning technique to detect people in dynamic scenes. The classification is purely based on the people shape and not on its image content. First motion information is used for detecting the objects of interest. Haar wavelets are used to represent the images and, finally, a supervised three layer neural network is used to classify the patterns.

Configurable Design of Multimodal Non Visual Interfaces for 3D VE's

3D virtual environments (VE) require an advanced user interface to fully express their information contents. New I/O devices enable the use of multiple sensorial channels (vision, hearing, touch, etc.) to increase the naturalness and the efficiency of complex interactions. Haptic and acoustic interfaces extend the effective experience of virtual reality to visually impaired users. For these users, a multimodal rendering that matches the subjective characteristics and the personal abilities of individuals is mandatory to provide a complete and correct perception of the virtual scene. User feedbacks are critical since the design phase. This paper proposes an approach for the design of haptic/acoustic user interface to makes up the lack of visual feedback in blind users interaction. It increases the flexibility of the interface development by decoupling the multimodal rendering design from the VE geometric structure. An authoring tool allows experts of the knowledge domain (even without specific skills about the VE) to design the haptic/acoustic rendering of virtual objects.

Influence of in vitro digestion process on polyphenolic profile of skin grape (cv. Italia) and on antioxidant activity in basal or stressed conditions of human intestinal cell line (HT-29)

White table grape cv. Italia is a typical component of the Mediterranean diet and a source of phenolic compounds, particularly abundant in the skin portion. The aim of this study was to characterize the phenolic profile of the table grape skin and to assess its stability after the in vitro digestion process. The main phenolic compounds identified by the HPLC-DAD analysis were: procyanidin B1, caftaric acid, catechin, coutaric acid, quercetin 3-glucuronide and quercetin 3-glucoside. All compounds showed a good stability after in vitro digestion (from 43 to 80%). Moreover, the influence of grape skin polyphenols on the modulation of ROS and GSH levels was evaluated in basal and in stressed conditions on human intestinal cells (HT-29). In basal conditions, a higher polyphenol concentrations exerted pro-oxidant effect corresponding to high ROS level and low GSH content. This effect was probably due to the polyphenolic oxidation in cell culture condition with consequent production of hydrogen peroxide. Otherwise, in stressed conditions, grape skin polyphenols exerted antioxidant effects up to 1.3 × 10-6 μg/g and restored the stress-related GSH reduction. The in vitro digestion process attenuated the biological effect of grape skin polyphenols on intestinal cell line (HT-29). In conclusion, grape skin polyphenols showed different behavior in relation to their concentrations and to the intracellular ROS levels.

Path planner with vision capability

In this paper we are going to describe an ongoing research project intended to integrate a full vision system in a flexible robot programming environment. The use of the vision system sensors, allows the robot to derive a description of the work cell. This description is used for the collision avoidance problem of robot manipulators. The work cell in assembly context can include moving objects. Without any previous knowledge of the work space, the vision system thus immediately determines the work cell map in its entirely. Successively this map is used as input for the path planner process to find the collision-free path. During the assembly robot operation, the vision system is activated to reflect any changes in the robot environment. In this way the path planner works recursively, updating the collision free path until the goal is reached.

A Heterogeneous Robotic Network for Distributed Ambient Assisted Living

Networks of robots and sensors have been recognized to be a powerful tool for developing fully automated systems that monitor environments and daily life activities in Ambient Assisted Living applications. Nevertheless, issues related to active control of heterogeneous sensors for high-level scene interpretation and mission execution are still open. This work presents the authors’ ongoing research about the design and implementation of a heterogeneous robotic network that includes static cameras and multi-sensor mobile robots for distributed target tracking. The system is intended to provide robot-assisted monitoring and surveillance of large environments. The proposed solution exploits a distributed control architecture to enable the network to autonomously accomplish general-purpose and complex monitoring tasks. The nodes can both act with some degree of autonomy and cooperate with each other. The chapter describes the concepts underlying the designed system architecture and presents the results of simulations performed in a realistic scenario to validate the distributed target tracking algorithm. Preliminary experimental results obtained in a real context are also presented showing the feasibility of the proposed system.

A supervised approach in background modelling for visual surveillance

In this paper we address the context of visual surveillance in outdoor environments involving the detection of moving objects in the observed scene. In particular, a reliable foreground segmentation, based on a background subtraction approach, is explored. We firstly address the problem arising when small movements of background objects, as trees blowing in the wind, generate false alarms. We propose a background model that uses a supervised training for coping with these situations. In addition, in real outdoor scenes the continuous variations of lighting conditions determine unexpected intensity variations in the background model parameters. We propose a background updating algorithm that work on all the pixels in the background image, even if covered by a foreground object. The experiments have been performed on real image sequences acquired in a real archeological site.