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  1. O. Lanz,
    Modeling Interactions in Multiple Object Bayesian Tracking,
    This paper proposes a framework for modeling interactions in muliple object 3D Bayesian tracking. It exploits both the computational cheapness of independent single object filters and the modeling power of the joint filter. Sampling from complex joint propagation densities is avoided by introducing interaction a posteriori, after blind single object propagation has been performed. To deal with occlusions for each object a support layer is computed. It contains probabilistic information about how likely a pixel is occluded by another object. Utilized to give less weight to likely occluded pixels, it provides the basis of a robust likelihood model. The implementation of the proposed ideas in a Sequential Monte Carlo framework are discussed. Experiments on a synthetic data show the robustness of the proposed ideas,
  2. S. Messelodi; C. M. Modena; M. Zanin,
    A computer vision system for the detection and classification of vehicles at urban road intersections,
    This paper presents a real-time vision system to compute traffic parameters by analyzing monocular image sequences from pole-mounted video cameras at urban crossroads.
    The system is flexible with respect to road geometry and camera position, permitting data collection from several monitored crosses. It uses a combination of segmentation and motion information to localize and track moving objects on the road plane, utilizing background subtraction and a feature-based tracking methodology. For each detected vehicle, the system is able to describe its path, to estimate its speed and to classify it into seven categories. The classification task relies on a model-based matching technique refined by a feature-based one.
    Experimental results demonstrate robust, real-time vehicle detection, tracking and classification over several hours of videos taken under different illumination conditions. The system is presently under trial in Trento, a one hundred thousand people town in northern Italy
  3. Roberto Brunelli,
    A Classification Case Study: People Identity Verification Based on Finger Matching,
    This paper aims at comparing Support Vector Machines with Gaussian kernels to Hyper Basis Functions networks, a variant of Regularization Networks, with a small number of units. The comparison is performed on the task of personal identity verification using dorsal images of fingers, coupling geometrical and textural information,
  4. C. Corridoni; M. Zanin,
    High Curvature Two-Clothoid Road Model Estimation,
    Road recognition is of fundamental importance for many image understanding tasks involving cameras mounted on moving vehicles. In this paper we consider the well-known approach to road recognition based on a clothoid road model. In the case of high curvature roads this approach shows its limitations. We propose an extended road model that covers explicitly the possibility of having two different clothoid segments in the camera field of view. An algorithm estimating parameters of both clothoids and their transition point is presented and tested in a simulated environment,
  5. G. Cattoni; S. Messelodi; C. M. Modena,
    Vision-based bicycle/motorcycle classification with Support Vector Machines,
    Classification of vehicles plays an important role in a traffic monitoring system. In this paper we present a feature-based classifier, which can distinguish bicycles from motorcycles in real world traffic scenes.
    Basically, the algorithm extracts some visual features focusing on the region corresponding to the wheels of vehicle. It splits the problem into two sub-cases depending on the computed motion direction. The classification is performed by means of a non-linear Support Vector Machine. Tests lead to a successful classification rate of 93% on video sequences taken from different road junctions in an urban environment
  6. C. Andreatta,
    CBIR techniques for object recognition,
    Content Based Image Retrieval (CBIR) is a widely adopted method for retrieving images from unannotated databases which are similar to a given query image. Usually images are indexed on the basis of low level features that can be automatically computed from the image visual content. Object detection and classification is a mandatory requirement for systems aiming at deriving semantic descriptions typically used by hymans to understand images. In this paper a novel approach is presented for object classification wihich is based on the extension of COMPASS, a CBIR system developed at ITC-irst. The experimental results are illustrated along with a comparison with a SVM classification approach recently proposed,
  7. C. Andreatta; M. Lecca; S. Messelodi,
    Memory based object recognition in images,
    MEMORI is a system for the detection and recognition of objects, stored in a database, within digital images taken as an input. It aims to provide a content-based indexing scheme which exploits the semantic information contained in the images. Object detection is achieved by segmenting the input image using color and textural information, and grouping the obtained regions by analyzing their adjacency relationships and their visual similarity to the objects in the database. The database is the memory of the system and consists of objects depicted by a set of different views, each of them described by a feature vector encoding color, texture and shape information. The same description is computed for the region groups candidated to represent an object and is compared, by an object classifier, with the database objects. The final result is a number of image regions each associated to one or more object classes with a confidence score,
  8. Alessandro Santuari; Oswald Lanz; Roberto Brunelli,
    Synthetic Movies for Computer Vision Applications,
    Proceedings of the Third IASTED International Conference on Visualization, Imaging, and Image Processing,
    , pp. 139-
  9. Filippo Bertamini; Roberto Brunelli; Oswald Lanz; Alessandro Roat; F. Santuari; Q. Xu Tobia,
    Olympus: an Ambient Intelligence Architecture on the Verge of Reality,
    Proceedings of the 12th International Conference on Image Analysis and Processing [ICIAP 2003],
    , pp. 139-
  10. Michele Zanin; Stefano Messelodi; Carla Maria Modena,
    Mantova, Italy,
    17/09/2003 - 19/09/2003,