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In this paper we propose an approach that utilizes visual features and conventional text-based pseudo-relevance feedback (PRF) to improve the results of semantic-theme-based video retrieval. Our visual reranking method is based on an Average Item Distance (AID) score. AID-based visual reranking is designed to improve the suitability of items at the top of the initial results list, i.e., those feedback...
An adaptive, invariant to user performance fluctuation or noisy input signal, gesture recognition scheme is presented based on Self Organizing Maps, Markov Models and Levenshtein sequence distance. Multiple modalities, all based on the hand position during gesturing, train different classifiers which are then fused in a weak classifier boosting-like setup by weight assignment to each stream. The adaptability...
This research proposes a nonlinear combination of an ensemble of classifiers to improve pattern recognition performance. A maritime target recognition application is considered. A database of radar range profiles with six ship classes from various aspect angles were created. Five structurally based features are defined on the simulated range profiles. Three kinds of classifiers are used: neural network,...
In this study we present a new approach to analyze and classify ECG signals for diagnosis of five cardiac conditions. Instead of following the conventional approach of beat-to-beat classification, we classify cardiac rhythms/segments of ECG based on statistical and morphological features extracted from them. We select and extract seven suitable features and reduce our feature space by using PCA and...
This paper presents a novel method for human recognition using gait information. The moving object position at first is detected by using the difference of two continuous frames. And then, based on the detected moving object, all of gait information was exploited. Based on the head shoulder and back contour, the walking direction can be extracted. Depend on this parameter, the lateral or frontal characteristic...
An innovative technique used for categorizing motion pictures and television shows based on motion activity is presented. First, scenes extracted from digitally stored movies and television programs are segmented into separate clips based on various editing effects such as hard cuts, fades and dissolves. Next,the initial frame of the sequence is automatically segmented into meaningful objects using...
A brain computer interface (BCI) is a communication system, which translates brain activity into commands for a computer or other devices. Nearly all BCIs contain as a core component a classification algorithm, which is employed to discriminate different brain activities using previously recorded examples of brain activity. In this paper, we study the classification accuracy achievable with a k-nearest...
Intelligent Space or iSpace is a new kind of computing system aiming at improving the environments of humans, creating a natural and easy to use solution. Its main feature is that the intelligence is not implemented separately in the actors, but it is distributed in the whole space. In this paper, we present a hand gesture and movement recognition system, whose purpose is to be used as an intuitive...
Efficient and effective feature extraction algorithms are required in the analysis of long records electrocardiographic (ECG) signals. In this paper a computationally efficient method is proposed as a feature extractor for P waves in ECG signals. The performance of the proposed algorithm was tested on 29 records of the MIT/BIH Arrhythmia Database resulting in 0.72% incorrectly detected P waves.
To identify a person using his/her handwriting; it is necessary to analyze a set of handwritings. Because of special styles of Persian handwritten; identifying Persian handwriting needs different approaches in compare with to other languages. This paper introduces a writer identification method to identify the writer of a Persian handwritten text. In the proposed method, the fuzzy approach is applied...
The multi-model recognition has been considered the development trend for the fast-developing biological recognition technology. Taking humanity cranio-maxillo-facial as the target, a novel recognition method is proposed in this paper. Starting from the mathematical model based on extracting characteristic parameters, the types of characteristic parameters is determined, and the features of different...
Objects like field lines and players are important for semantic analysis in soccer video. In this paper, we propose effective methods for field lines and players detection and recognition. Regions of field lines and players are first segmented from shot of wide angle view. Gray value top-hat transform is then performed on the segmented region to detect field lines. Mid-lines, end-lines and penalty-lines...
Intonation assessment is an important part of Chinese CALL system. Nowadays, most systems use the correlation and RMSE features to assess the quality of the intonation of a given speech. As correlation and RMSE assign unoptimized weights to different degrees of mismatching errors, they may lead to performance degradation. In this paper, we propose a new feature called sorted error vector (SEV) for...
In this paper, we present an approach, called FREQDIST, for speaker segmentation based on a distance measurement applied in the frequency domain. To enhance the detection performance, the spectrum is reweighted using normalization techniques. Additionally, noise-like (i.e. flat) spectra are removed based on the entropy. Experiments using the TIMIT database [1] and Westdeutscher Rundfunk broadcast...
In this paper, we investigate the fusion of several features extracted from manually-labelled silhouettes. A novel approach for human gait recognition based on the combination of three discriminative features, i.e., the area, the gravity centre, and the orientation of each body component, is also proposed. Experimental results show that the proposed method exhibits considerably better performance,...
Feature extraction is an important topic in machine learning. There are two representative criterions for feature extraction, i.e. Fisher Criterion and Maximum Margin Criterion. In this paper, we propose a new criterion, called Regular Simplex Criterion. This criterion requires that samples from the same class are projected to the same point, while samples from different classes have unit distance...
This paper investigates geometric feature extraction from scanned image and applies it in multi-view image registration. The presented registration approach includes three steps, feature extraction, coarse registration and fine registration. Firstly, feature points are identified based on curvature estimation, and feature point linkage is set up according to neighboring relationship of the extracted...
This paper presents a novel biometric recognition system fusing the palmprint and hand geometry of a human hand based on morphology. We utilize the image morphology and concept of Voronoi diagram to cut the image of the front of the whole palm apart into several irregular blocks in accordance with the hand geometry. Furthermore, statistic characteristics of the gray level in the blocks are employed...
The method described in this paper deals with the problems of T-wave detection in ECG signals. Determining the position of a T-wave can be complicated, due to the ambiguous and changing form of the complex and the presence of noise. We developed a method to detect T-waves in noisy signals. The performance of the proposed method was tested on 33 records of the MIT/BIH arrhythmia database resulting...
Spatial structure of objects is an important feature of images and making use of this feature properly is very important for the user in the retrieval system. However, only a third of the existing image retrieval systems use spatial features and those features are low precision features which are variant to rotation and shift. In this paper, a polygon-based spatial feature model is proposed to describe...
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