introduction to extract and combine information from different modalities, fusion techniques are commonly applied to promote system performance. in this study, we aimed to examine the effectiveness of fusion techniques in emotion recognition. materials and methods electrocardiogram (ecg) and galvanic skin responses (gsr) of 11 healthy female students (mean age: 22.73±1.68 years) were collected ...

The goal of this paper is to describe an exploration system for large image databases in order to help the user understand the database as a whole, discover hidden relationships, and formulate insights with minimum effort. While the proposed system works with any type of low-level feature representation of images, we describe our system using color information. The system is built in three stag...

The hypothesis veri cation stage of the traditional image processing approach, consisting of low, medium, and high level processing, will su er if the set of low level features extracted are of poor quality. We investigate the optimisation of the feature extraction chain by using Genetic Algorithms. The tness function is a performance measure which re ects the quality of an extracted set of fea...

Much of the world’s supply of data is in the form of time series. In the last decade, there has been an explosion of interest in mining time series data. A number of new algorithms have been introduced to classify, cluster, segment, index, discover rules, and detect anomalies/novelties in time series. While these many different techniques used to solve these problems use a multitude of differen...

This paper describes our experiments for the high level feature extraction task in TRECVid 2007. We submitted the following five runs: • A jr1 1: Baseline run using early fusion of all input features. • A jr1 2: Classic early feature fusion and concept correlation. • A jr1 3: Classic late feature fusion. • A jr1 4: Late feature fusion and concept correlation. • A jr1 5: Early fusion of heuristi...

In this paper we propose a novel feature extraction scheme for texture classi cation, in which the texture features are extracted by a two-level hybrid scheme by integrating two statistical techniques of texture analysis. In the rst step, the low level features are extracted by the Gabor lters, and they are encoded with the feature map indices using the Kohonen's SOFM algorithm. In the next ste...

In this work an adaptive method for accurate and robust grouping of local features belonging to planes of interior scenes and object planar surfaces is presented. For arbitrary set of images acquired from different views, the method organizes a huge number of local SIFT features to fill the gap between low-level vision (front end) and high level vision, i.e. domain specific reasoning about geom...

Real-world videos often contain dynamic backgrounds and evolving people activities, especially for those web videos generated by users in unconstrained scenarios. This paper proposes a new visual representation, namely scene aligned pooling, for the task of event recognition in complex videos. Based on the observation that a video clip is often composed with shots of different scenes, the key i...

The present work is a part of research study aiming to develop an algorithm and a software system capable of quick identification of weapons and relations between human and a weapon in a scene. Bridging the semantic gap between the low level knowledge extracted from an image and the high level semantics needed to negotiate the weapon domain ontology is connected to the features extraction algor...

We present an approach for the treatment of Feature Interactions in Intelligent Networks. The approach is based on the formal description technique Estelle and consists of three steps. For the rst step, a speci cation style supporting the integration of additional features into a basic service is introduced. As a result, feature integration is achieved by adding speci cation text, i.e. on a pur...