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With rapid growth of LTE network and Voice-over-LTE(VoLTE), detecting and preventing security threats like Denial of Service attack becomes a necessary and urgent requirement. VoLTE is an voice solution based on Internet Protocol and 4G LTE technology, at the same time exposing many vulnerabilities when using packet-switched network. There are many heavy weighted detection systems using content analysis,...
In this paper, we present an automatic system of mine like object detection and recognition for sonar videos. This system is implemented with two main methods. One is the object detection and segmentation with intrackability, another is object recognition of mine like based on improved BOW algorithm and Support Vector Machine (SVM). Intrackability is defined by the concept of entropy, and can reflect...
Information fusion is a key research area widely applied to various multimedia analysis tasks such as artificial intelligence, humancomputer interaction, robotics, distributed computing, financial systems and security/surveillance. Feature level fusion has been considered as the most promising fusion method due to the rich information presented at this level. A critical operation of feature level...
Hand shape recognition method based on geometric features uses individual information limitedly and inadequately. To solve this problem, this paper proposes a hand shape recognition method based on contour features of fingers. Firstly, we separate the four fingers and use curve fitting method to position the axis of finger. Then the matched fingers are normalized by translation and rotational alignment,...
This paper aims at providing a general method for feature extraction and recognition. The most essential issues for pattern recognition include extracting discriminant features and improving recognition accuracy. Kernel Entropy Component Analysis (KECA), as a new method for data transformation and dimensionality reduction, has attracted more attentions. However, as KECA only reveals structure relating...
Moving vehicle detection in dynamical scene is a significant but challenging problem in these days. A new and effective approach to extract moving vehicles is proposed in this paper. In our method, Harris corner and Lucas-Kanade (L-K) optical flow was adopted to generalize feature-point optical flow field between two consecutive frames which obtained from monocular moving camera, and then vector quantization...
In face recognition, there are great challenges with variations arising from illumination, expression and other factors. Since the fractional Fourier transform feature is robust to illumination and expression variations and has been used in face recognition area, we propose a novel algorithm to face recognition with the local region histogram of the two dimensional fractional Fourier transform (2D-FrFT)...
In this paper, it presents a novel approach for selecting discriminative features in multimodal information fusion based discriminative multiple canonical correlation analysis (DMCCA), which is the generalized form of canonical correlation analysis (CCA), multiple canonical correlation analysis (MCCA) and discriminative canonical correlation analysis (DCCA). The proposed approach identifies the discriminative...
Multiple Maximum scatter difference (MMSD) discriminant criterion is an effective feature extraction method that computes the discriminant vectors from both the range of the between-class scatter matrix and the null space of the within-class scatter matrix. However, singular value decomposition (SVD) of two times is involved in MMSD, making this method impractical for high dimensional data. In this...
Physical activity has a positive impact on people's well-being and it can decrease the occurrence of chronic disease. To date, there has been a substantial amount of research studies, which focus on activity recognition using accelerometer and gyroscope-based sensors. However, many of these studies adopt a single sensor approach and focus on proposing novel features combined with complex classifiers...
Fractional Fourier Transform (FRFT) is a time-frequency analysis tool which contains the time-frequency information of the signal at the same time. In this paper, we use FRFT as feature extraction method for recognizing smile emotion. Based on the FRFT, the original signal is transformed into complex-values containing amplitude and phase information. We adopt to use amplitude, phase and complex information...
In this paper, we present a statistical analysis of six traffic features based on entropy and distinct feature number at the packet level, and we find that, although these traffic features are unstable and show seasonal patterns like traffic volume for a long period, they are stable and consistent with Gaussian distribution in a short time period. However, this equilibrium property will be violated...
Computer recognition of human emotional states is an important component for efficient human-computer interaction. In this paper we explore an approach for recognition of human emotion from the visual information. We perform feature selection by using the two dimensions fractional Fourier transform. As a generalization of Fourier transform, the two dimensions fractional Fourier transform (2D-FrFT)...
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