Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
In order to have a rich representation for human action, we propose to combine two complementary features so that a human posture can be characterized in more details. In particular, the distance signal feature and the width feature are combined in an effective way to enhance each other's discriminating capability. The resulting feature vector is quantized into mid-level features using k-means clustering...
This paper presents a novel scheme for human action recognition. First of all, we employ the curvature estimation to analyze human posture patterns and to yield the discriminative feature sequences. The feature sequences are further represented into sets of strings. Consequently, we can solve human action recognition problem by the string matching technique. In order to boost the performance of string...
This paper presents a human action recognition method using histogram of oriented gradient (HOG) of motion history image (MHI). First, the proposed method generates MHI with differential images which are obtained by frame difference of successive frames of a video. The histogram of oriented gradient (HOG) of the MHI is then computed. Finally, support vector machine (SVM) is applied to train an action...
For plate detection, we found that when the plate is disturbed by complex upright borderlines, location can be inaccurate or even missed. On the basis of this, a new vehicle license plate location algorithm based on salient feature is introduced. It makes use of the texture feature, geometric characteristics and color information. By raw location and precise location, it can quickly locate the license...
A novel interactive segmentation method based on distance metric learning is proposed for segmentation of tumors in CT and MRI images. Firstly, the moments of the gray-level histogram are extracted as the image features for segmentation. Then, Neighborhood Components Analysis is employed to learn a task-specific distance metric in the feature space using the interactive inputs. The probability of...
The descriptive power of low-level image features for describing the high-level semantic concepts is limited for content-based image retrieval (CBIR). To reduce this semantic gap and improve retrieval performance of CBIR, a distance metric learning method is proposed which can learn a linear projection to define a distance metric for maximizing mean average precision (MAP). The smooth approximation...
In data mining and pattern classification, feature extraction and representation methods are a very important step since the extracted features have a direct and significant impact on the classification accuracy. In literature, numbers of novel feature extraction and representation methods have been proposed. However, many of them only focus on specific domain problems. In this article, we introduce...
In this paper, a content-based audio retrieval method is proposed, which can quickly detect and locate similar sound in audio database. We extract a chroma-based audio feature: chromagram, a variation on time-frequency distributions, which represents the spectral energy at each of 12 pitch classes. Compared with traditional feature MFCC (Mel Frequency Cesptral Coefficient), chromagram is better when...
This paper presents a novel approach to achieve optimization for the audio features in compressed domain, which is the PSO (particle swarm optimization) algorithm basing on the attribute importance criterion of rough set theory. Our method firstly extracts the attributes of audio to form the feature vectors and pre-processes these vectors, then realizes the optimization using the proposed PSO algorithm,...
Considering noise interference often exists in audio processing, it is not robust enough to calculate audio similarity by using distance measure directly. In this paper, basing on Renyi's quadratic entropy, a novel scheme for audio similarity measure is proposed. In our work, we extract Mel Frequency Cepstral Coefficients (MFCCs) to represent each audio, and then calculate the similarity based on...
This paper introduces a system that can recognize different type of paper-folding by users. The system allows users to register and use their desired paper in the interaction, and detect the folding by using Speed Up Robust Feature (SURF) algorithm. The paper also describes a paper-based tower defense game which has been developed as a proof of concept of our method. This method can be considered...
This paper addresses an old, yet challenging issue - curvature estimation from discrete sampling points over a curve. We introduce a novel algorithm based on performing line integrals. The proposed method is computationally more efficient than the previous integration-based methods because of the constant computation time. Qualitative tests on synthesized shapes in the presence of noise are performed,...
Mean shift algorithm has grained great success in object tracking domain due to its ease of implementation, real time response and robust tracking performance, however, the fixed kernel bandwidth may cause tracking failure for size changing objects. A novel object tracking algorithm for FLIR imagery is proposed based on mean shift with adaptive bandwidth. The scale invariant feature transform is employed...
The problem of recognizing multiple object classes in natural images has proven to be a difficult challenge for compute vision. It is reasonable to look to biology for inspiration, a novel multiclass object recognition algorithm based on a biologically inspired model named ST model is proposed. ST model is based on the theory of biological neurology, which calculates object features that exhibit position...
Gastroscopy is important tool for the clinical examination of gastric diseases, and the abnormality detection on the gastroscopic images will help physicians to diagnose. An improved patches assembled by local weights is presented in this paper. First, a series of classifiers on image patches with different sizes have been analyzed to find the suitable size. The boosted stumps are employed as the...
This paper has accomplished an improved local accumulate histogram method of Thangka Image Retrieval. First, change the color space from RGB to HSV and divide similar area by the value of the hue reasonably, then it can get six similar intervals which the hue (H) is independent of the value (V) (Saturation (S) is assumed a constant in the beginning). Second, accumulate histogram is applied respectively...
A novel layered object tracking algorithm for FLIR imagery is proposed based on mean shift algorithm and feature matching. First, infrared object is modeled by kernel histogram. Bhattacharyya coefficient is used to measure the similarity between object model and candidate model. The object is then localized by mean shift algorithm rapidly and efficiently. Because of the low contrast between infrared...
A method, referred to as Composite of Central and Ring Projection (CCRP), is proposed to extract features with rotation invariant property. It reduces the dimensionality of a two-dimensional pattern by performing both central projection (CP) and ring projection (RP). A dissimilarity function is developed and used to distinguish different patterns. This function makes use of both similarity corrections...
A novel fuzzy clustering based target extraction algorithm for FLIR imagery using spatio-temporal technique is presented. Firstly, in temporal domain, we establish the Gauss distribution model of frame difference background by incorporating the motion information of the target. And then, the infrared target region is determined based on change detection mask. Secondly, in spatio domain, the improved...
In the medical diagnosis, the false negative prediction is more serious than the false positive prediction. We introduce the cost-sensitive rule ensemble method (RuleFit) to breast ultrasound, which can induce the interpretable scoring rules for malignancy assessment, and can be applied to tune the sensitivity and specificity of the predictive model by varying the cost weights of misclassification...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.