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With the development of the economic and the popularity of smartphones, location-based service is receiving more and more attention. It can be used inside a building where GPS signals are often unavailable. Because of its low deployment cost, vision-based indoor localization is becoming popular in the complicated indoor environment. However, in order to increase the accuracy of indoor localization,...
Image based indoor localization is an important problem with many useful application. This paper proposes an indoor localization system for performing fine localization and less latency with more priori information, including tile angel and the relative height between camera optical center and origin in reference coordinate system (RCS). The system is divided into two stages: offline stage and online...
Visual-based indoor localization have become a favored research area in recent years. It can be used inside a building where GPS signals are often not available. And due to its low deployment cost, visual-based indoor localization has been implemented in the complicated indoor environment. However, in order to increase the accuracy of indoor localization, the scale of image database should be as large...
As some public buildings have become large in spatial scale, people find it more and more difficult to know their actual location in these buildings. Generally in the indoor environment, to get location information is relatively more complex than that in the outdoor environment, for traditional outdoor localization methods do not perform well in indoor environment. Under this circumstances, image...
Vision based localization is an essential problem for many applications, such as augmented reality and pedestrian navigation. In this paper, a visual location recognition system based on multi-sensor information is proposed. In this system, a database called visual map is established before the localization stage. The visual map contains the visual features and the corresponding positional features...
In this paper, we first propose a novel no-reference (NR) image quality assessment (IQA) method for retargeted image based on the rank learning approach. Firstly, image features for each retargeted image are extracted, which should not only represent the image characteristics but also be sensitive to the retargeted distortions. Specifically, the image feature should be able to capture the shape distortions,...
Aiming the mental tasks recognition tasks in brain computer interface (BCI), this paper proposes an Electroencephalography (EEG) feature extraction method which makes use of the discriminative common spatial patterns (CSP). Apart from CSP analysis's traditional application in time domain, it is extended to consider frequency domain information of EEG signal. After an artifact removal through the independent...
Although a number of features derived from linear speech production theory have been investigated as speech emotion indicators, the recognition accuracy still stays unsatisfactory for realistic applications. In this paper, Teager Mel, a novel speech emotion feature is proposed based on Teager Energy Operator (TEO) and the Mel perception characteristics. Due to such advantages as nonlinear and simple,...
Human exhibits great capacity in processing various kinds of complex and conflicting speeches in high interference acoustic scenes like cocktail party and many other public environments. Discovery of the auditory cognitive conflict control mechanism has great inspiration to automatic speech recognition (ASR) system design. The present research investigated the auditory cognitive conflict control mechanism...
Perceptual quality evaluation of the retargeting image plays an important role in benchmarking different retargeting methods, as well as guiding or optimizing the retargeting process. The distortions introduced during the retargeting process are mainly categorized into shape distortion and content information loss [1]. The shape distortion measurement is critical to the evaluation of retargeting image...
Robust and accurate spectral analysis for electroencephalogram (EEG) signal becomes more and more essential and crucial in psychological and neural studies. The traditional fixed precision Fourier Transform (FT) cannot well reveal the subtle difference and characteristics among individuals. In this paper, a Constant Q Transform (CQT) based approach for EEG spectral analysis was proposed in order to...
In this paper, an effective reduced reference (RR) video quality assessment (VQA) is proposed by depicting both the spatial and temporal statistical characteristics of the video signals. For each video frame, spatial information change (SIC) is employed to depict the energy variation. A novel mutual masking strategy based on the extracted SIC is proposed to accurately simulate the human visual system...
Much attention has been paid to WLAN indoor positioning algorithm for its high accuracy and low cost to meet the location based services (LBS). This paper proposes a novel positioning algorithm based on positioning characteristics extraction in WLAN indoor environment. Each RSS signal from an individual access point is taken as input of the RBF neural networks to establish the mapping between RSS...
Different kinds of features in time domain, spectral domain and cepstral domain are used for musical genre classification. In this paper, through the fusion of short-term timbral features and long-term rhythmic feature, we propose a novel method where: musical genre vector is constructed using the likelihood ratio of GMM (Gaussian Mixture Model) and radar chart is applied to provide visualized style...
The goal of steganography is to hide information into media without disclosing the fact of existing communication. Currently, stganography such as least significant bit (LSB), quantization index modulation (QIM) and spread spectrum (SS), has become increasingly widespread. Steganalysis as a counterpart of stganography is to detect the presence of it. In this paper, we present a new universal steganalysis...
The visualization of medical volumetric data is an important area of scientific visualization. 3-D segmentation plays a critical role by facilitating automatic or semi-automatic extraction of the anatomical organ or region-of-interest. Segmentation s an important aspect of medical image processing, whose purpose is to extract the region of interest from the original images to provide a reliable basis...
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