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The optical flow is widely used in detection and dynamic analysis of moving objects, but it has the heavy computational burden, so it has not been able to in the real-time progress needs. Cellular Neural Network is a kind of neural network with outstanding image processing capabilities, and can be utilized in real-time applications. This paper presents an optical flow analysis method based on CNN,...
In this paper, we further develop the idea of subject specific mental tasks selection process as a necessary prerequisite in any EEG-based brain computer interface (BCI) application. While, in two previous researches we proved - using the EEG-extracted auto-regressive (AR) parameters and twelve different mental tasks -, the major gains one can obtain in tasks classification performance only by selecting...
Augmented reality aims to insert virtual objects in real scenes. In order to obtain a coherent and realistic integration, these objects have to be relighted according to their positions and real light conditions. They also have to deal with occlusion by nearest parts of the real scene. To achieve this, we have to extract photometry and geometry from the real scene. In this paper, we adapt high dynamic...
Lipreading is applied to synthesize speech for the speech-impaired people. To get a higher recognition result, data fusion with weighting coefficients at feature level is used to integrate the lip information from different kinds of lip features. Experiments are carried out based on HMM with different states and Gaussian mixture component in a small database for speaker-dependent case. Experiment...
Tracking multiple objects in surveillance scenarios involves considerable difficulty because of occlusions. We report a novel tracker - based on reliability tracking - that demonstrates superior performance under high degrees of occlusion. In our method, distinguishable features between the target and non-target are represented as the object's reliability. When the selected features are no longer...
The thesis proposes a hybrid intrusion detection model based on the parallel genetic algorithm and the rough set theory. Due to the difficult for the status of intrusion detection rules. This model, taking the advantage of rough set's streamline the edge to data and genetic algorithm's high parallelism, succeeds in introducing the genetic-rough set theory to the instrusion detection. The application...
In this paper, we solve the searching problem by high level features used by sign language recognition. Firstly, we find the face in video frames that has complex background, and then we find the left sign and right sign in specific areas. By computing the signs' length, position, velocity, acceleration, Fourier figure descriptor and etc, we generate the signs' dynamic features. Consequently, we segment...
Object tracking based on color feature often fails in a complex background. To deal with this problem, a particle filtering object tracking approach is proposed in this paper based on local binary pattern and color feature. Color histogram is the global description of targets in color image, while local binary pattern texture contains information of neighbor region texture in gray image. These two...
This paper describes and deduces the theory of Haar-like features, Integral image and AdaBoost algorithm, which were proposed by Paul Viola, and then researches its improvement. We combine Microsoft Visual C++6.0 with OpenCV Function library to develop the software, and achieve the function of real-time face detection. According to experimental results, we can conclude that the improved algorithm...
An N-gram modeling approach for unstructured audio signals is introduced with applications to audio information retrieval. The proposed N-gram approach aims to capture local dynamic information in acoustic words within the acoustic topic model framework which assumes an audio signal consists of latent acoustic topics and each topic can be interpreted as a distribution over acoustic words. Experimental...
Efficient data mining and indexing is important for multimedia analysis and retrieval. In the field of large-scale video analysis, effective genre categorization plays an important role and serves one of the fundamental steps for data mining. Existing works utilize domain-knowledge dependent feature extraction, which is limited from genre diversification as well as data volume scalability. In this...
This paper presents a link between the well known Common Spatial Pattern (CSP) algorithm and Riemannian geometry in the context of Brain Computer Interface (BCI). It will be shown that CSP spatial filtering and Log variance features extraction can be resumed as a computation of a Riemann distance in the space of covariances matrices. This fact yields to highlight several approximations with respect...
In many applications it is necessary to be able to classify images in a database accurately and with acceptable speed. The main problem is to assign different images to right categories. The later problem becomes more challenging while dealing with large databases with many categories and subcategories. In this paper we propose a novel classification method based on an adopted hierarchical Dirichlet...
We propose a new time-space acoustical feature for fast video copy detection to search a video segment for a number of video streams to find illegal video copies on Internet video site and so on. We extract a small number of feature vectors from acoustically peculiar points that express the point of local maximum/minimum in the time sequence of acoustical power envelopes in video data. The relative...
Cyclostationary detection is regarded as a major method for spectrum sensing in cognitive radio and other applications as well. The rationale behind the detection is that the second order statistic of the interested signal is periodical. The period is therefore used as the critical feature for detection. In practice, due to clock error or oscillator error or other errors, the detector is hardly able...
Cognitive radio (CR) is a promising technology for improving the utilization of the scarce radio spectrum by allowing secondary users to regularly sense the spectrum and opportunistically access the under-utilized frequency bands. However, spectrum sensing in CR environment is a challenging task due to varying radio channel conditions and might lead to interference with licensed users. In this paper,...
Real time traffic such as voice and video have strict requirements on the acceptable end-to-end packet delay. When there are different types of traffic with different requirements on tolerable latency, priority based packet scheduling schemes are normally used in order to reduce the queuing delay for real time services. However, in cognitive radio networks, the time that the system spends on spectrum...
Recently, the IEEE 802 working groups for regional, local, metropolitan, and personal area networks undertake standardization of cognitive radio (CR) networks exploiting TV white spaces. Thus, in the near future, various types of IEEE 802 CR systems may operate on the same TV channel simultaneously. A CR system can coexist more effectively with other CR systems on the same TV channel if it can identifies...
Autonomous Surveillance is an important term in order to produce pervasive, ubiquitous, homenet, telemetics and other application purposes. However, many surveillance systems are annoyed with some environmental hazards like illumination and others. This paper presents a novel method for non-intrusive biometric vision system for the surveillance having the prior knowledge about environment. As an environment...
Gesture input interfaces for mobile devices with a touch screen have become widespread. Although gesture interfaces in common use are limited to the small screens of these mobile devices, pointing interfaces for large screens using handheld devices or attachments are common. However, these devices increase the user's cognitive load because they are unable to cancel the effect of spatial cognition...
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