The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Background modeling and subtraction are essential to video surveillance applications. There are two main issues related to background modeling: how to initialize the background model, and how to update the model based on observations. In this paper, we consider the first issue with the aim of generating a clear background image that does not contain foreground objects or noise. We used a bidirectional...
This paper describes the evaluation of the Auto-Adaptive Parallel Neural Network Architecture, AAPNNA, in the SBMnet dataset. AAPNNA is an artificial neural model based on two networks whose neurons represent two different Background models that adapt their parameters at different rates. A very important feature of AAPNNA is its capacity to auto adapt to new scenario conditions as demonstrated with...
The link prediction is a classical problem for computer science and many other research fields. Existing link prediction methods mainly apply the link patterns for the network in order to predict future possible links. However, in a network generated by the human interaction, the links may not only relate to the observed datasets, but also are affected by the decisions of human. That is to say, this...
The key challenge of face recognition is to develop effective feature representations for reducing intra-personal variations while enlarging inter-personal differences. This paper presents a novel non-linear discriminant error criterion which can be used in effective feature learning from raw pixels. Unlike many existing methods which assume the problem to be linear in nature, the proposed method...
Deriving semantic 3D models of man-made environments hitherto has not reached the desired maturity which makes human interaction obsolete. Man-made environments play a central role in navigation, city planning, building management systems, disaster management or augmented reality. They are characterised by rich geometric and semantic structures. These cause conceptual problems when learning generic...
In scene analysis, the availability of an initial background model that describes the scene without foreground objects is at the basis of many computer vision applications. Multi-modal models of the scene background are frequently adopted in the applications, where each mode tries to keep track of the multiple background modes observed along the sequence. In this work we specifically address the problem...
Linear regression is a standard statistical method widely used for prediction. It focuses on modeling the mean the target variable without accounting for all the distributional properties of this variable. In contrast, the quantile regression model facilitates the analysis of the full distributional properties, it allows to model different quantities of the target variable. This paper proposes a quantile...
Object detection and localization in images involve a multi-scale reasoning process. First, responses of object detectors are known to vary with image scale. Second, contextual relationships on a part-level, object-level, and scene-level appear at different scales of the image. This paper studies efficient modeling of these two components by training multi-scale template models. The input to the proposed...
In this paper, we present a novel method for constructing a generative model to analyze the structure of labeled data. Given a time-series of sample graphs, we aim to learn a so-called “supergraph” that best describes the underlying average connectivity structure presenting in the data. In this time-series the vertex set is fixed and labeled and the set of possible connections between vertices change...
Older adults who have never used smartphone often suffers from getting used to smartphone gestures because of their lack of basic knowledge or skills with the latest technologies like gesture-oriented touchscreens. In this paper, we propose a user modeling method for inferring problems novice users face for smartphone from their touchscreen gestures. The output of user model is used by automated help...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.