0000000000055613
AUTHOR
Luca Greco
Characterization of MEMS accelerometer self-noise by means of PSD and Allan Variance analysis
In this paper, we have studied the sources of error of a low-cost 3-axis MEMS accelerometer by means of Power Spectral Density and Allan Variance techniques. These techniques were applied to the signals acquired from ten identical devices to characterize the variability of the sensor produced by the same manufacturer. Our analysis showed as identically produced accelerometer have somehow variable behavior in particular at low frequency. It is therefore of paramount importance before their use in Inertial Navigation or Earthquakes Monitoring System, a complete characterization of each single sensors.
Steering dynamical systems with finite plans and limited path length
Complex dynamical systems can be steered by using symbolic input plans. These plans must have a finite descriptive length, and can be expressed by means of words chosen in an alphabet of symbols. In this way, such plans can be sent through a limited capacity channel to a remote system, where they are decoded in suitable control actions. The choice of this symbols is essential to efficiently encode steering plans. To this aim, in this paper, we state the problem of finding symbols maximizing the interval of points reachable by the system along paths with constrained length. We focus on the problem with two symbols, and compare the results with those produced by plans not accounting for the l…
Object Recognition and Modeling Using SIFT Features
In this paper we present a technique for object recognition and modelling based on local image features matching. Given a complete set of views of an object the goal of our technique is the recognition of the same object in an image of a cluttered environment containing the object and an estimate of its pose. The method is based on visual modeling of objects from a multi-view representation of the object to recognize. The first step consists of creating object model, selecting a subset of the available views using SIFT descriptors to evaluate image similarity and relevance. The selected views are then assumed as the model of the object and we show that they can effectively be used to visual…
Saliency Based Aesthetic Cut of Digital Images
Aesthetic cut of photos is a process well known to professional photographers. It consists of cutting the original photo to remove less relevant parts close to the borders leaving in this way the interesting subjects in a position that is perceived by the observer as more pleasant. In this paper we propose a saliency based technique to automatically perform aesthetic cut in images. We use a standard method to estimate the saliency map and propose some post processing on the map to make it more suitable for our scope. We then apply a greedy algorithm to determine the cut (i.e. the most important part of the original image) both in the cases of free and fixed aspect ratio. Experimental result…
A Decisional Multi-Agent Framework for Automatic Supply Chain Arrangement
In this work, a multi-agent system (MAS) for supply chain dynamic configuration is proposed. The brain of each agent is composed of a Bayesian Decision Network (BDN); this choice allows the agent for taking the best decisions estimating benefits and potential risks of different strategies, analyzing and managing uncertain information about the collaborating companies. Each agent collects information about customer's orders and current market prices, and analyzes previous experiences of collaborations with trading partners. The agent therefore performs a probabilistic inferential reasoning to filter information modeled in its knowledge base in order to achieve the best performance in the sup…
Views selection for SIFT based object modeling and recognition
In this paper we focus on automatically learning object models in the framework of keypoint based object recognition. The proposed method uses a collection of views of the objects to build the model. For each object the collection is composed of N×M views obtained rotating the object around its vertical and horizontal axis. As keypoint based object recognition using a complete set of views is computationally expensive, we focused on the definition of a selection method that creates, for each object, a subset of the initial views that visually summarize the characteristics of the object and should be suited for recognition. We select the views by determining maxima and minima of a function, …
AUTOMATIC ORGANIZATION OF MULTIMEDIA DATA COLLECTIONS
La fotografia digitale ha avuto uno sviluppo sempre crescente negli ultimi dieci anni. Prima la diminuzione dei prezzi delle apparecchiature di acquisizione e poi l’integrazione di queste nei dispositivi portatili di uso quotidiano (i.e. smartphone, tablet) ha permesso a chiunque di potere creare e conservare semplicemente un enorme numero di immagini. Inoltre l’immagine stessa é diventata uno strumento di comunicazione, portando alla nascita di social networks basati unicamente sulla condivisione di fotografie (flickr, instagram, etc...). La gestione di tali quantitá di dati é quindi diventato un problema reale per molti utenti, in quanto il ritrovamento e l’organizzazione di questi dati é…
Video object recognition and modeling by SIFT matching optimization
In this paper we present a novel technique for object modeling and object recognition in video. Given a set of videos containing 360 degrees views of objects we compute a model for each object, then we analyze short videos to determine if the object depicted in the video is one of the modeled objects. The object model is built from a video spanning a 360 degree view of the object taken against a uniform background. In order to create the object model, the proposed techniques selects a few representative frames from each video and local features of such frames. The object recognition is performed selecting a few frames from the query video, extracting local features from each frame and looki…
Why you trust in visual saliency
Image understanding is a simple task for a human observer. Visual attention is automatically pointed to interesting regions by a natural objective stimulus in a first step and by prior knowledge in a second step. Saliency maps try to simulate human response and use actual eye-movements measurements as ground truth. An interesting question is: how much corruption in a digital image can affect saliency detection respect to the original image? One of the contributions of this work is to compare the performances of standard approaches with respect to different type of image corruptions and different threshold values on saliency maps. If the corruption can be estimated and/or the threshold is fi…
360° Tracking Using a Virtual PTZ Camera
Object tracking using still or PTZ cameras is a hard task for large spaces and needs several devices to completely cover the area or to track multiple subjects. The introduction of \(360^{\circ }\) camera technology offers a complete view of the scene in a single image and can be useful to reduce the number of devices needed in the tracking problem. In this paper we present a framework using \(360^{\circ }\) cameras to simulate an unlimited number of PTZ cameras and to be used for tracking. The proposed method to track a single target process an equirectangular view of the scene and obtains a model of the moving object in the image plane. The target is tracked analyzing the next frame of th…
Empirical Likelihood-Based ANOVA for Trimmed Means
In this paper, we introduce an alternative to Yuen’s test for the comparison of several population trimmed means. This nonparametric ANOVA type test is based on the empirical likelihood (EL) approach and extends the results for one population trimmed mean from Qin and Tsao (2002). The results of our simulation study indicate that for skewed distributions, with and without variance heterogeneity, Yuen’s test performs better than the new EL ANOVA test for trimmed means with respect to control over the probability of a type I error. This finding is in contrast with our simulation results for the comparison of means, where the EL ANOVA test for means performs better than Welch’s heteroscedastic…
Symbolic control for underactuated differentially flat systems
In this paper we address the problem of generating input plans to steer complex dynamical systems in an obstacle-free environment. Plans considered admit a finite description length and are constructed by words on an alphabet of input symbols, which could be e.g. transmitted through a limited capacity channel to a remote system, where they can be decoded in suitable control actions. We show that, by suitable choice of the control encoding, finite plans can be efficiently built for a wide class of dynamical systems, computing arbitrarily close approximations of a desired equilibrium in polynomial time. Moreover, we illustrate by simulations the power of the proposed method, solving the steer…