Application of artificial vision techniques in different spectral domains

L'applicazione di tecniche di visione artificiale in diversi domini spettrali è argomento molto trattato in letteratura. L'approccio che abbiamo deciso di seguire riguarda l'applicazione di alcune tra tali tecniche in situazioni poco affrontate dai lavori precedenti e con uno sguardo rivolto a quanto avviene nel sistema visivo umano, cercando di sopperire alle carenze valutative tipiche di un sistema artificiale che tenta di emularne uno naturale, anche con l'impiego di sensori che forniscono immagini dal contenuto informativo diverso rispetto a quello che caratterizza le immagini percepibili dall'occhio. Sono state effettuate tre sperimentazioni, impiegando sensori operanti nelle tre regioni dello spettro elettromagnetico che risultano abitualmente utilizzate nell'ambito della visione artificiale: visibile, NIR e FIR. Obiettivo comune delle sperimentazioni è stato individuare oggetti, anche se di natura diversa, nelle immagini acquisite: pedoni e veicoli, nel caso della prima indagine; solo pedoni, nella seconda, ed oggetti generici nella terza. Per ogni sperimentazione, le ricerche sono state condotte concentrando l'attenzione sull'aspetto che, dall'osservazione delle immagini, abbiamo ritenuto più significativo per la discriminazione degli oggetti all'interno delle immagini stesse da parte del nostro sistema visivo di osservatori umani. Così, ci è sembrato che il movimento potesse essere l'aspetto distintivo degli oggetti nelle immagini acquisite per la prima sperimentazione, mentre la forma è stata ritenuta la caratteristica più idonea alla trattazione della seconda e, per la terza, il colore degli oggetti rispetto a quello di sfondo.The application of artificial vision techniques in different spectral domains is a very popular subject in literature. The approach we chose has to do with the application of some of them among those techniques in situations not very much dealt with in previous works. Seeing what happens in the human visual system, trying to face eventual shortcomings typical of an artificial system that attempts to emulate a natural one, also with the employment of sensors that provide images with a different informative content in respect of that which characterizes the images as perceived by the eye. Three experiments have been performed using sensors working the three electromagnetic spectrum regions that are usually employed in artificial vision: visible, near infrared and far infrared. The common purpose of the experiments was to detect different kinds of objects in the acquired images: pedestrians and vehicles in the first investigation, pedestrians only in the second one and generic obstacles in the third. For each experiment, research has been conducted concentrating attention on those aspects which, looking at the images, we thought to be the most significant in discriminating objects by our visual system of human observers. Thus we thought that movement would be the distinctive aspect of objects in acquired images for the first experiment, whereas shape seemed to be the most appropriate characteristic for the second one. For the third one, the colour of objects in respect to being part of the background

The BRAiVE Autonomous Ground Vehicle Platform

The interest in having an autonomous vehicle platform is driven by the long term objective, aimed by many research centers, of changing the transportation system world to move people in a safer and more efficient way. The BRAiVE vehicle presented in this paper is designed for this goal and with the idea of reaching it trough a series of steps, each one introducing more advanced systems and more complex levels of automation. A section describing the state of the art in this field introduces the paper showing the features of other similar projects around the world and pointing out BRAiVE's innovations. The paper focuses on the technical aspects involved in this project. Starting from the design choices, such as sensor placement, coverage or actuators performance, going trough development issues and solutions adopted to reach a high integration level for preserving the external look together with good ergonomics for the interiors. Conclusions collect the demonstrations in which effectiveness and the versatility of the vehicle has been shown

A 13,000 km Intercontinental Trip with Driverless Vehicles: The VIAC Experiment

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Obstacle Detection with Stereo Vision for Off-Road Vehicle Navigation

In this paper we present an artificial vision algorithm for real-time obstacle detection in unstructured environments. The images have been taken using a stereoscopical vision system. The system uses a new approach, of low computational load, to calculate a V-disparity image between left and right corresponding images, in order to estimate the cameras pitch oscillation caused by the vehicle movement. Then, the obstacles are localized by stereo matching and mapped in real world coordinates. Experimental results on sequences taken from a moving vehicle (which partecipated to the DARPA Grand Challenge 2004) in different unstructured scenarios are then presented, to demonstrate the validity of the approach

Fedriga, “A Decision Network Based Frame-work for Visual Off-Road Path Detection Problem

Abstract — This paper describes a Decision Network based frame-work used for path-detection algorithm development in autonomous vehicle applications. Lane marker detection algorithms do not work in off-road environments. Off-road trails have too much complexity, with widely varying textures and many differing natural boundaries. The authors have developed a general approach. Images are segmented into regions, based on the homogeneity of some pixel properties and the resulting regions are classified as road or not-road by a Decision Network Process. Combinations of contiguous clusters form the path surface, allowing any arbitrary path to be represented. I

Automatic Calibration of a Urban Video Surveillance System through the Observation of Zebra Crossings

In this paper, a method for automatic calibration of a camera stereo pair through the observation of zebra crossing signs is described. It is based on the well-known consideration that it is possible to obtain information about lens distortion and camera orientation by observing how a known pattern appears in the image; moreover, a major advantage of this system is that it does not require any ad-hoc calibration pattern, because it exploits the zebra crossing signs, a pattern usually present in images used for monitoring pedestrians while crossing a road. To achieve this goal, well-known techniques for removing lens distortion and perspective effect are combined with new methods for locating calibration points on the available pattern, and, finally, for evaluating the camera position

A 13.000 km intercontinental trip with driverless vehicles: the VIAC experiment

In recent years the interest in autonomous vehicles has incrementally increased. After the DARPA Challenges new fields of application as agricultural, construction, mining, and also nautical are continuously opening up. In this paper a huge test is presented, the first of this kind in the history of vehicular robotics. A trip from Italy to China with four electric autonomous vehicles will be described focusing on all aspects of the challenge, from the managing issues to the most technical ones. A vehicle-following application (or virtual towing) is the system under test for a three consecutive months and 13,000 km long unique experience

Obstacle detection with stereo vision for off-road vehicle navigation. Paper presented at the

In this paper we present an artificial vision algorithm for real-time obstacle detection in unstructured environments. The images have been taken using a stereoscopical vision system. The system uses a new approach, of low computational load, to calculate a V-disparity image between left and right corresponding images, in order to estimate the cameras pitch oscillation caused by the vehicle movement. Then, the obstacles are localized by stereo matching and mapped in real world coordinates. Experimental results on sequences taken from a moving vehicle (which partecipated to the DARPA Grand Challenge 2004) in different unstructured scenarios are then presented, to demonstrate the validity of the approach. 1

Pedestrian Detection in Poor Visibility Conditions: Would SWIR Help?Image Analysis and Processing

The 2WIDE SENSE (WIDE spectral band & WIDE dynamics multifunctional imaging SENSor Enabling safer car transportation) EU funded project is aimed at the development of a low-cost camera sensor for Advanced Driver Assistance Systems (ADAS) applications able to acquire the full visible to Short Wave InfraRed (SWIR) spectrum from 400 to 1700 nm. This paper presents the first results obtained by investigating the SWIR contribution to pedestrian detection in difficult visibility conditions as haze and fog employing the wide-bandwidth camera developed within the project