Search results for "artificial intelligence"
showing 10 items of 6122 documents
Why you trust in visual saliency
2015
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…
Exploiting Correlation between Body Gestures and Spoken Sentences for Real-time Emotion Recognition
2017
Humans communicate their affective states through different media, both verbal and non-verbal, often used at the same time. The knowledge of the emotional state plays a key role to provide personalized and context-related information and services. This is the main reason why several algorithms have been proposed in the last few years for the automatic emotion recognition. In this work we exploit the correlation between one's affective state and the simultaneous body expressions in terms of speech and gestures. Here we propose a system for real-time emotion recognition from gestures. In a first step, the system builds a trusted dataset of association pairs (motion data -> emotion pattern), a…
Emo-dramatic Robotic Stewards
2010
In this paper will be presented an heterogeneous colony of robots capable to cooperate with people as effective partners to provide different kind of support among various working environments, such as museums, offices or trade fairs. Many systems have been integrated in order to develop robots capable to assists humans during the visit of the site, to guide them and to give information about the environment. According to the drama’s theory, each robot has a different character, something like a personality, so, each of them will interact with people in a different way. Robots show also emotional, non trivial, behaviours using an LSA conceptual space capable to synthesize the different emot…
TSVD as a Statistical Estimator in the Latent Semantic Analysis Paradigm
2015
The aim of this paper is to present a new point of view that makes it possible to give a statistical interpretation of the traditional latent semantic analysis (LSA) paradigm based on the truncated singular value decomposition (TSVD) technique. We show how the TSVD can be interpreted as a statistical estimator derived from the LSA co-occurrence relationship matrix by mapping probability distributions on Riemanian manifolds. Besides, the quality of the estimator model can be expressed by introducing a figure of merit arising from the Solomonoff approach. This figure of merit takes into account both the adherence to the sample data and the simplicity of the model. In our model, the simplicity…
A Novel Visual Interface to Foster Innovation in Mechanical Engineering and Protect from Patent Infringement
2018
One of the main time and money consuming tasks in the design of industrial devices and parts is the checking of possible patent infringements. Indeed, the great number of documents to be mined and the wide variety of technical language used to describe inventions are reasons why considerable amounts of time may be needed. On the other hand, the early detection of a possible patent conflict, in addition to reducing the risk of legal disputes, could stimulate a designers' creativity to overcome similarities in overlapping patents. For this reason, there are a lot of existing patent analysis systems, each with its own features and access modes. We have designed a visual interface providing an …
A Conceptual Probabilistic Model for the Induction of Image Semantics
2010
In this paper we propose a model based on a conceptual space automatically induced from data. The model is inspired to a well-founded robotics cognitive architecture which is organized in three computational areas: sub-conceptual, linguistic and conceptual. Images are objects in the sub-conceptual area, that become "knoxels" into the conceptual area. The application of the framework grants the automatic emerging of image semantics into the linguistic area. The core of the model is a conceptual space induced automatically from a set of annotated images that exploits and mixes different information concerning the set of images. Multiple low level features are extracted to represent images and…
Human Activity Recognition Process Using 3-D Posture Data
2015
In this paper, we present a method for recognizing human activities using information sensed by an RGB-D camera, namely the Microsoft Kinect. Our approach is based on the estimation of some relevant joints of the human body by means of the Kinect; three different machine learning techniques, i.e., K-means clustering, support vector machines, and hidden Markov models, are combined to detect the postures involved while performing an activity, to classify them, and to model each activity as a spatiotemporal evolution of known postures. Experiments were performed on Kinect Activity Recognition Dataset, a new dataset, and on CAD-60, a public dataset. Experimental results show that our solution o…
Super-resolution-based magnification of endothelium cells from biomicroscope videos of the cornea
2018
We present a practical, robust, and effective pipeline to compute a high-resolution (HR) image of the corneal endothelium starting from a low-resolution (LR) video sequence obtained with a general purpose slit lamp biomicroscope. An image quality typical of dedicated and more expensive confocal microscopes is achieved via software magnification by exploiting information redundancy in the video sequence. In particular, the HR image is generated from the best LR frames, obtained by identifying the most suitable endothelium video subsequence using a support vector machine-based learning approach, followed by a robust graph-based frame registration. Results on long, real sequences show that the…
Springs-based Simulation for Image Retargeting
2011
In this paper an efficient method for image retargeting is pro- posed. It relies onto a mechanical model based on springs network. Each pixel displacement (compression or expan- sion) is given by the network response, according to the springs stiffness. The properties of the springs are deter- mined as function of the visual relevance of the pixels. Such model does not require any optimization, since its so- lution is obtained simply from a linear system of equations, allowing real-time application even for large images. The approach is fully automatic, though can be improved by interactively providing cues such as geometric constraints and/or manual relevant object labeling. The results pr…