Search results for "RECOGNITION"
showing 10 items of 3607 documents
Multi-modal biometric authentication systems
2010
The main goal of a biometric system is to discriminate automatically subjects in a reliable and dependable way, accordingly to a specific target application. The discrimination is based on one or more types of information derived from physical or behavioural traits, such as fingerprint, face, iris, voice, hand, or signature. Applications of biometrics range from homeland security and border control to e-commerce and e-banking, including secure networking and authentication. Traditionally, biometric systems working on a single biometric feature, have many limitations, such as, trouble with data sensors, where captured sensor data are often affected by noise, distinctiveness ability, because …
Noise Filtering Using Edge-Driven Adaptive Anisotropic Diffusion
2008
This paper presents a method aimed to noise removal in MRI (Magnetic Resonance Imaging). We propose an improvement of Perona and Malik's anisotropic diffusion filter. In our schema, the diffusion equation of the filter has been modified to take into account the edges direction, This allows the filter to blur uniform areas, while it better preserves the edges. Both quantitative and qualitative evaluation is presented and the results are compared with other methods.
A Structural Approach to Infer Recurrent Relations in Data
2014
Extracting knowledge from a great amount of collected data has been a key problem in Artificial Intelligence during the last decades. In this context, the word "knowledge" refers to the non trivial new relations not easily deducible from the observation of the data. Several approaches have been used to accomplish this task, ranging from statistical to structural methods, often heavily dependent on the particular problem of interest. In this work we propose a system for knowledge extraction that exploits the power of an ontology approach. Ontology is used to describe, organise and discover new knowledge. To show the effectiveness of our system in extracting and generalising the knowledge emb…
A Topic Recognition System for Real World Human-Robot Conversations
2013
One of the main features of social robots is the ability to communicate and interact with people as partners in a natural way. However, achieving a good verbal interaction is a hard task due to the errors on speech recognition systems, and due to the understanting the natural language itself. This paper tries to overcome such kind of problems by presenting a system that enables social robots to get involved in conversation by recognizing its topic. Through the use of classical text mining approach, the presented system allows social robots to understand topics of conversation between human partners, enabling the customization of behaviours in their accordance. The system has been evaluated …
Pedestrian Tracking in 360 Video by Virtual PTZ Cameras
2018
Since the data acquired by a PTZ camera change while adjusting the pan, tilt and zoom parameters, the results of tracking algorithms are difficult to reproduce; such diffi- culty limits the development and the comparison of tracking algorithms with PTZ cameras. The recently introduced 360- degree cameras acquire spherical views of the environment, generally stored as equirectangular images. Each pixel of an equirectangular image corresponds to a point on the spherical surface. A gnomonic projection can be used to project the points on the spherical surface onto a plane tangent to the sphere. Such tangent plane can be interpreted as the image plane of a virtual PTZ camera oriented towards th…
Real-time content-aware image resizing using reduced linear model
2010
In this paper an effective and efficient method for contentaware image resizing is proposed. It is based on the solution of a linear system where each pixel displacement (compression or expansion) is determined in dependence of the visual relevance of the pixel itself. The linear nature of the model allows real-time application of the method even for large images. This fully automatic approach can be also improved by interactively providing cues such as geometric constraints and/or manual relevant object labeling. The results have proven that the presented method achieves results comparable or superior to existent strategies, while improving efficiency.
Texture Synthesis for Digital Restoration in the Bit-Plane Representation
2007
In this paper we propose a new approach to handle the problem of restoration of grayscale textured images. The purpose is to recovery missing data of a damaged area. The key point is to decompose an image in its bit-planes, and to process bits rather than pixels. We propose two texture synthesis methods for restoration. The first one is a random generation process, based on the conditional probability of bits in the bit-planes. It is designed for images with stochastic textures. The second one is a best-matching method, running on each bit-plane, that is well suited to synthesize periodic patterns. Results are compared with a state-of-the-art restoration algorithm.
Hankelet-based dynamical systems modeling for 3D action recognition
2015
This paper proposes to model an action as the output of a sequence of atomic Linear Time Invariant (LTI) systems. The sequence of LTI systems generating the action is modeled as a Markov chain, where a Hidden Markov Model (HMM) is used to model the transition from one atomic LTI system to another. In turn, the LTI systems are represented in terms of their Hankel matrices. For classification purposes, the parameters of a set of HMMs (one for each action class) are learned via a discriminative approach. This work proposes a novel method to learn the atomic LTI systems from training data, and analyzes in detail the action representation in terms of a sequence of Hankel matrices. Extensive eval…
Wi-Dia: Data-Driven Wireless Diagnostic Using Context Recognition
2018
The recent densification of Wi-Fi networks is exacerbating the effects of well-known pathologies including hidden nodes and flow starvation. This paper provides an automatic diagnostic tool for detecting the source roots of performance impairments by recognizing the wireless operating context. Our tool for Wi-Fi diagnostic, named Wi-Dia, exploits machine learning methods and uses features related to network topology and channel utilization, without impact on regular network operations and working in real-time. Real-time per-link Wi-Fi diagnosis enables recovering actions for context-specific treatments. Wi-Dia classifier recognizes different classes of interference; it is jointly trained us…
An evaluation of recent local image descriptors for real-world applications of image matching
2019
This paper discusses and compares the best and most recent local descriptors, evaluating them on increasingly complex image matching tasks, encompassing planar and non-planar scenarios under severe viewpoint changes. This evaluation, aimed at assessing descriptor suitability for real-world applications, leverages the concept of approximated overlap error as a means to naturally extend to non-planar scenes the standard metric used for planar scenes. According to the evaluation results, most descriptors exhibit a gradual performance degradation in the transition from planar to non-planar scenes. The best descriptors are those capable of capturing well not only the local image context, but als…