Baobin Li

Interpolatory quad/triangle subdivision schemes for surface design

Recently the study and construction of quad/triangle subdivision schemes have attracted attention. The quad/triangle subdivision starts with a control net consisting of both quads and triangles and produces finer and finer meshes with quads and triangles. The use of the quad/triangle structure for surface design is motivated by the fact that in CAD modelling, the designers often want to model certain regions with quad meshes and others with triangle meshes to get better visual quality of subdivision surfaces. Though the smoothness analysis tool for regular quad/triangle vertices has been established and C^1 and C^2 quad/triangle schemes (for regular vertices) have been constructed, there is no interpolatory quad/triangle schemes available in the literature. The problem for this is probably that since the template sizes of the local averaging rules of interpolatory schemes for either quad subdivision or triangle subdivision are big, an interpolatory quad/triangle scheme will have large sizes of local averaging rule templates. In this paper we consider matrix-valued interpolatory quad/triangle schemes. In this paper, first we show that both scalar-valued and matrix-valued quad/triangle subdivision scheme can be derived from a nonhomogeneous refinement equation. This observation enables us to treat polynomial reproduction of scalar-valued and matrix-valued quad/triangle schemes in a uniform way. Then, with the result on the polynomial reproduction of matrix-valued quad/triangle schemes provided in our accompanying paper, we obtain in this paper a smoothness estimate for matrix-valued quad/triangle schemes, which extends the smoothness analysis of Levin-Levin from the scalar-valued setting to the matrix-valued setting. Finally, with this smoothness estimate established in this paper, we construct C^1 matrix-valued interpolatory quad/triangle scheme (for regular vertices) with the same sizes of local averaging rule templates as those of Stam-Loops quad/triangle scheme. We also obtain C^2 matrix-valued interpolatory quad/triangle scheme (for regular vertices) with reasonable sizes of local averaging rule templates.

Balanced Multifilter Banks for Multiple Description Coding

The parametrization for one kind of multifilter banks generating balanced multiwavelets is presented in this paper, in which two lowpass filters are flipping filters, and two highpass filters have linear phase. Based on these parametric expressions, some balanced multiwavelets and analysis-ready multiwavelets are constructed, which are symmetric, or antisymmetric. Moreover, on the basis of balanced multiwavelet transform, a new method of multiple description coding is given, and experiments show that this method works well. Compared with the traditional multiple description coding method, this method has low redundancy.

BALANCED INTERPOLATORY MULTIWAVELETS WITH MULTIPLICITY r

Vector-valued refinable interpolatory functions with multiplicity r are discussed in this paper. This kind of refinable functions have a sampling property like Shannons sampling theorem, and corresponding matrix-valued refinable masks possess special structure. In the context of multiwavelets, some properties of multifilter banks related will be present. Based on these properties, it will be shown that there are no symmetric (or antisymmetric) vector-valued refinable functions with interpolatory property. In the practical application, multiwavelets are always required to possess a certain degree of smoothness, which is related to three different concepts: balancing order, approximation order and analysis-ready order. In the general case, three notions are different. But if the scaling function is interpolatory, three concepts will be verified to equal to each other. Finally, a complete characterization of multifilter banks {H, G} will also be given and it will be used to construct some new balanced multiwavelets with interpolatory property for case r = 2, corresponding to which, multifilter banks have rational coefficients.

Balanced Multiwavelets With Interpolatory Property

Balanced multiwavelets with interpolatory property are discussed in this paper. This kind of multiwavelets can have a sampling property like Shannons sampling theorem. It has been shown that the corresponding matrix-valued refinable mask has special structure, and an orthogonal multifilter bank {H(z),G(z)} can be reduced to a scalar valued conjugate quadrature filter (CQF) a(z) . But it does not mean that any scalar CQF can form a “good” multifilter bank which can generate a vector-valued refinable function with some degree of smoothness. In the context of balanced multiwavelets, we give the definition of transferring balance order, which a scalar CQF a(z) satisfies, to guarantee that the multiwavelet Ψ generated is balanced. On the basis of the parametrization of a scalar CQF with any length and conditions of transferring balance order, parametrization of multifilter banks which can generate interpolatory multiwavelet and interpolatory scaling function, is gotten. Moreover, some balanced interpolatory multiwavelets have been constructed. Interpolatory analysis-ready multiwavelets (armlets) are also discussed in this paper. It is known that conditions of armlets are easy to validate, compared with balanced multiwavelets. But it will be present that if the corresponding scaling function Φ is interpolatory, the multiwavelet Ψ is balanced of order n if and only if it is an armlet of order n. Finally, the application of balanced multiwavelets with interpolatory property in image processing is also discussed.

Emotion recognition using Kinect motion capture data of human gaits

Automatic emotion recognition is of great value in many applications, however, to fully display the application value of emotion recognition, more portable, non-intrusive, inexpensive technologies need to be developed. Human gaits could reflect the walker’s emotional state, and could be an information source for emotion recognition. This paper proposed a novel method to recognize emotional state through human gaits by using Microsoft Kinect, a low-cost, portable, camera-based sensor. Fifty-nine participants’ gaits under neutral state, induced anger and induced happiness were recorded by two Kinect cameras, and the original data were processed through joint selection, coordinate system transformation, sliding window gauss filtering, differential operation, and data segmentation. Features of gait patterns were extracted from 3-dimentional coordinates of 14 main body joints by Fourier transformation and Principal Component Analysis (PCA). The classifiers NaiveBayes, RandomForests, LibSVM and SMO (Sequential Minimal Optimization) were trained and evaluated, and the accuracy of recognizing anger and happiness from neutral state achieved 80.5% and 75.4%. Although the results of distinguishing angry and happiness states were not ideal in current study, it showed the feasibility of automatically recognizing emotional states from gaits, with the characteristics meeting the application requirements.

ORTHOGONAL WAVELET TRANSFORM OF SIGNAL BASED ON COMPLEX B-SPLINE BASES

In this paper, an orthogonal wavelet transform of signal based on complex B-spline bases is given. The new wavelet transform realizes accurate computation of coefficients of complex B-spline base functions. It integrates good properties of orthogonality, symmetry and continuity, and offers better approximations to continuous signal than do the Haar wavelet and Daubechies wavelets. All algorithms of the new orthogonal wavelet transform are based on explicit formulas and easy to be implemented.

Visualization Analysis for Big Data in Computational CyberPsychology

This paper discusses issues related to the big data in Computational CyberPsychology, and proposes to utilize Parallel Coordinates, an famous method in the field of information visualization, to improve analyzing data. The experimental results show that Parallel Coordinates will be very helpful and give visual analyzing of big data in studying of Computational CyberPsychology.

The Personality Analysis of Characters in Vernacular Novels by SC-LIWC

There are many researches on psychological text analysis, and it has been proved that the words people use can reflect their emotional states. In this paper, we introduce how to analyze the psychology of the characters in vernacular novels automatically. First, we process the dialogs with word segmentation, and analyze the segmented text with SC-LIWC. Then, a vector reflecting the psychology of the character is obtained and we map it to the big five. Finally, taking the dialogs of the Journey to the West as corpus, We have got the personalities of four main characters which are verified to be same as some famous comments of the Journey to the West, which shows that our work is effective.

Speech Emotion Recognition Using Local and Global Features

Speech is an easy and useful way to detect speakers’ mental and psychological health, and automatic emotion recognition in speech has been investigated widely in the fields of human-machine interaction, psychology, psychiatry, etc. In this paper, we extract prosodic and spectral features including pitch, MFCC, intensity, ZCR and LSP to establish the emotion recognition model with SVM classifier. In particular, we find different frame duration and overlap have different influences on final results. So, Depth-First-Search method is applied to find the best parameters. Experimental results on two known databases, EMODB and RAVDESS, show that this model works well, and our speech features are enough effectively in characterizing and recognizing emotions.

Predicting Depression from Internet Behaviors by Time-Frequency Features

Early detection of depression is important to improve human well-being. This paper proposes a new method to detect depression through time-frequency analysis of Internet behaviors. We recruited 728 postgraduate students and obtained their scores on a depression questionnaire (Zung Self-rating Depression Scale, SDS) and digital records of Internet behaviors. By time-frequency analysis, we built classification models for differentiating higher SDS group from lower group and prediction models for identifying mental status of depressed group more precisely. Experimental results show classification and prediction models work well, and time-frequency features are effective in capturing the changes of mental health status. Results of this paper might be useful to improve the performance of public mental health services.