Fenghua Guo

Haptic data compression based on quadratic curve reconstruction and prediction

In this paper, a novel haptic data compression method is presented. A linear prediction model based on a tangential direction concept is derived that adapts to local geometric changes of haptic data samples. The suggested data compression strategy further relies on a quadratic curve reconstruction strategy to improve signal approximation. Knowledge from human haptic perception is incorporated into the technique to ensure that compression artifacts remain imperceptible to the user. The experimental results demonstrated that the proposed haptic data reduction strategy can potentially outperform other related methods in the literature.

A Malicious Node Detection Algorithm Based on Principle of Maximum Entropy in WSNs

WSN is a distributed network exposed to an open environment, which is vulnerable to malicious nodes. To find out malicious nodes among a WSN with mass sensor nodes, this paper presents a malicious detection method based on maximum entropy model. Given the types of a few sensor nodes, it extracts sensor nodes’ preferences related with the known types of malicious node, establishes the maximum entropy model of all sensor nodes that participate in network activities. Then, according to the study on the type-known sensor nodes’ samples based on principle of maximum entropy, all of the unknown-type sensor nodes are classified, with probabilities of different types. The experiment results show that as long as the preferences of sensor nodes are precise and the number of active sensor nodes is stable, the detection rate of malicious nodes is stabilized over 90%.

Haptic data compression based on curve reconstruction

In this paper, the problem of haptic data compression is addressed. The algorithm partitions haptic data samples into subsets while relying on knowledge from human haptic perception. A geometric distance-based approach is used to reduce the number of haptic data subsets. In particular, to improve approximation precision, each haptic data subset is fitted by a quadratic curve. Accordingly, rather than directly using the original haptic data, only the coefficients of the quadratic curves are stored or transmitted. Experiments are performed to compare the suggested curve reconstruction method with the more common linear method. The results prove the effectiveness of the proposed approach in improving data reduction rate and approximation precision.

Sketching Interfaces for Remote Collaboration

Current systems for real-time distributed CSCW are largely rooted in traditional GUI-based groupware. These groupware applications generally lag behind in features and compatibility with single-user applications. As a result, having to learn new GUIs for a sporadic task discourages many users. Many researchers agree that TUIs (tangible user interfaces) are especially suited for collocated collaboration. We conclude that sketching with pencil and eraser together for early design is suited for remote collaboration and communication. Current sketching systems are largely for single-user and sketching with pencil. In this paper, we present a method supporting sketching with pencil and eraser together for remote collaboration.

Data Fitting by Quadratic Splines

In this paper the problem of data fitting using quadratic spline is addressed. An efficient algorithm is presented. Given a set of ordered planar points, the algorithm divides this set of points into subsets, while the data points in each subset are collinear within the given tolerance. The data points in each subset are fitted by a curve segment and all data points are fitted by a C1 quadratic spline curve. The algorithm is simple and reliable, decreases the number of fitting curve segments and maintains the approximating accuracy. This algorithm is tested and can be applied to reverse engineering and image curves fitting.

A Geometric Method for Subpixel Boundary

A new geometric method is presented for sub-pixel boundary extraction. Many existing methods can obtain boundary pixels, so this paper tries to locate accurately the object edge inside a pixel. Assuming that the boundary is straight line at a pixel size, the new method analyzes the neighboring pixels blurred by the boundary, and finds the boundary by a geometric method. It is proved that the result is accurate for the straight boundary edge. In addition, the new method is proved not to be sensitive to noise. Examples are given to compare the new method and interpolation method at last.

A New Piecewise Rational Reparameterization Method

A new piecewise rational re-parameterization of a polynomial curve is presented. The method relies on a parametric polygonal decomposition method. With the proposed piecewise rational re-parameterization method, the optimal parameterization can be reached, and the optimal parameterizations asymptotic convergence to the arc-length parameterization is analyzed. Computing instances demonstrates the efficiency of the proposed method.

Haptic Data Compression Based on Linear Prediction

A new linear prediction-based haptic data reduction technique is presented. The prediction approach relies on the least-squares method to reduce the number of data packets. Knowledge from human haptic perception is incorporated into the architecture to assess the perceptual quality of the compressed haptic signals. Experiments prove the effectiveness of the proposed approach in data reduction rate.

A new method for approximating optimal parameterization of polynomial curves

Rational re-parameterizations of a polynomial curve that preserve the curve degree and [0,1] parameter domain are characterized by a single degree of freedom. The optimal re-parameterization in this family can be identified but the existing methods may exhibit too much residual parametric speed variation for motion control and other applications. In this paper, a new re-parameterization method to optimal parameterization is presented and the optimal parameterization in this family obtained by the new method satisfies that the maximum deviation from unit-speed is the minimum. Experiments for comparing the efficiency of this algorithm with other methods are also included.

An Algorithm For Sketching Design with Pencil and Eraser

We have investigated interaction behavior with physical tools - pencil and eraser together in sketching design and conclude that interaction with pencil and eraser is more natural than with pen alone. We present a new algorithm supporting both sketching design and interaction with pencil and eraser just like designers naturally do on the paper. This interaction technique belongs to the most pervasive computing technology. The algorithm adopts a new data structure, which integrates data structure for image and graph. The graph modification and recognition is based on image along with dynamic information of strokes or context. Experiments for illustrating the efficiency of this algorithm are also included