2500181
Video object segmentation and tracking using /spl psi/-learning classification
As a requisite of the emerging content-based multimedia technologies, video object (VO) extraction is of great importance. This paper presents a novel semiautomatic segmentation and tracking method for single VO extraction. Unlike traditional approaches, the proposed method formulates the separation of the VO from the background as a classification problem. Each frame is divided into small blocks of uniform size, which are called object blocks if the centering pixels belong to the object, or background blocks otherwise. After a manual segmentation of the first frame, the blocks of this frame are used as the training samples for the object-background classifier. A newly developed learning tool called /spl psi/-learning is employed to train the classifier which outperforms the conventional Support Vector Machines in linearly nonseparable cases. To deal with large and complex objects, a multilayer approach constructing a so-called hyperplane tree is proposed. Each node of the tree represents a hyperplane, responsible for classifying only a subset of the training samples. Multiple hyperplanes are thus needed to classify the entire set. Through the combination of the multilayer scheme and /spl psi/-learning, one can avoid the complexity of nonlinear mapping as well as achieve high classification accuracy. During the tracking phase, the pixel in the center of every block in a successive frame is classified by a sequence of hyperplanes from the root to a leaf node of the hyperplane tree, and the class of the block is identified accordingly. All the object blocks thus form the object of interest, whose boundary unfortunately is stair-like due to the block effect. In order to obtain the pixel-wise boundary in a cost efficient way, a pyramid boundary refining algorithm is designed, which iteratively selects a few informative pixels for class label checking, and reduces uncertainty about the actual boundary of the object. The proposed method has been applied on video sequences with various spatial and temporal characteristics, and experimental results demonstrate it to be effective, efficient, and robust.
10569326
Intelligent compliant motion control
The role of a compliant motion scheme is to control a robot manipulator in contact with its environment. By accommodating with the interaction force, the manipulator can be used to accomplish tasks that involve constrained motions. This paper presents a new work on the compliant motion control for position-controlled manipulator. A new method for achieving efficient interaction between the manipulator and its environment is developed. The interaction force is reduced using a quadratic cost function. In this method, the compliance is formulated as function of the interaction force. An adaptive element is used to update the compliance. The stability of the system is investigated using the Lyapunov approach. Experiments are conducted in our laboratory to demonstrate the use of such scheme.
1196113
Feature-based wavelet shrinkage algorithm for image denoising
A selective wavelet shrinkage algorithm for digital image denoising is presented. The performance of this method is an improvement upon other methods proposed in the literature and is algorithmically simple for large computational savings. The improved performance and computational speed of the proposed wavelet shrinkage algorithm is presented and experimentally compared with established methods. The denoising method incorporated in the proposed algorithm involves a two-threshold validation process for real-time selection of wavelet coefficients. The two-threshold criteria selects wavelet coefficients based on their absolute value, spatial regularity, and regularity across multiresolution scales. The proposed algorithm takes image features into consideration in the selection process. Statistically, most images have regular features resulting in connected subband coefficients. Therefore, the resulting subbands of wavelet transformed images in large part do not contain isolated coefficients. In the proposed algorithm, coefficients are selected due to their magnitude, and only a subset of those selected coefficients which exhibit a spatially regular behavior remain for image reconstruction. Therefore, two thresholds are used in the coefficient selection process. The first threshold is used to distinguish coefficients of large magnitude and the second is used to distinguish coefficients of spatial regularity. The performance of the proposed wavelet denoising technique is an improvement upon several other established wavelet denoising techniques, as well as being computationally efficient to facilitate real-time image-processing applications.
33641222
Object tracking using the Gabor wavelet transform and the golden section algorithm
The paper presents an object tracking method for object-based video processing which uses a two-dimensional (2D) Gabor wavelet transform (GWT) and a 2D golden section algorithm. An object in the current frame is modeled by local features from a number of the selected feature points, and the global placement of these feature points. The feature points are stochastically selected based on the energy of their GWT coefficients. Points with higher energy have a higher probability of being selected since they are visually more important. The amplitudes of the GWT coefficients of a feature point are then used as the local feature. The global placement of the feature points is determined by a 2D mesh whose feature is the area of the triangles formed by the feature points. In this way, a local feature is represented by a GWT coefficient amplitude vector, and a global feature is represented by a triangle area vector. One advantage of the 2D mesh is that the direction of its triangle area vector is invariant to affine transform. Consequently, the similarity between two local features or two global features can be defined as a function of the angle and the length ratio between two vectors, and the overall similarity between two objects is a weighted sum of the local and global similarities. In order to find the corresponding object in the next frame, the 2D golden section algorithm is employed. Our results show that the method is robust to object deformation and supports object tracking in noisy video sequences.
15990035
Content-based retransmission for 3-D wavelet video streaming on the Internet
Improving the QoS of video streaming with packet loss is a challenging topic of research. In this paper, we propose a novel content-based retransmission scheme to address this issue. The basic idea is to jointly consider the packets' contents and the channel conditions to optimize QoS. The goal is to deliver the best quality of video possible under the same channel condition. Using the proposed retransmission scheme, we have designed a 3D wavelet video streaming system. Simulation results show that the content-based retransmission can improve the video quality by more than 2 dB compared with the existing non-content-based delay-constrained retransmission when the channel loss rate is high.
9136723
Biped Locomotion by Reduced Ankle Power
Power reduction in the ankle joints of a biped robot is considered inthis paper. Ankles of human beings have small torque and are veryflexible within a certain range of motion (very stiff near and beyondthis range). This characteristic makes foot landing soft and gives agood contact between its sole and the ground. This feature can beimplemented in a biped robot by using a small actuator for the anklejoints. A small actuator consumes less energy and reduces the weightof the leg. With less power in the ankle joints, robot walkingbecomes more difficult to control. This problem can be solved byproviding a feedback control mechanism as presented in this paper. Thecontrol mechanism uses the motion of the body and the swinging leg toeliminate instability caused by the weak ankle. Two locomotionexamples, standing and walking, were investigated respectively toshow the validity of the proposed control scheme. In standing, thecontrol input is the displacement of the ankle joint of thesupporting leg. The control mechanism decides the bending angle ofthe body and the position of the swinging leg. For walking, only thebending angle of the body is used to avoid the discontinuity of thecontrol input. Experimental results are presented to show theeffectiveness of the control mechanism.
14223982
Statistical Database Modeling for Privacy Preserving Database Generation
Testing of database applications is of great importance. Although various studies have been conducted to investigate testing techniques for database design, relatively few efforts have been made to explicitly address the testing of database applications which requires a large amount of representative data available. As testing over live production databases is often infeasible in many situations due to the high risks of disclosure of confidential information or incorrect updating of real data, in this paper we investigate the problem of generating synthetic database based on a-priori knowledge about production database. Our approach is to fit general location model using various characteristics (e.g., constraints, statistics, rules) extracted from production database and then generate synthetic data using model learnt. As characteristics extracted may contain information which may be used by attacker to derive some confidential information, we present a disclosure analysis method which is based on cell suppression technique. Our method is effective and efficient to remove aggregate private information during data generation.
462067
Compact and Flexible Resolution of CBT Multicast Key-Distribution
In an open network such as the Internet, multicast security services typically start with group session-key distribution. Considering scalability for group communication among widely-distributed members, we can find a currently-leading approach based on a CBT (Core-Based Tree) routing protocol, where Group Key Distribution Centers (GKDCs) are dynamically constructed during group-member joining process.
7069478
An Advantage of Low-Exponent RSA with Modulus Primes Sharing Least Significant Bits
Let N = pq denote an RSA modulus of length n bits. Call N an (m - LSbS) RSA modulus if p and q have exactly m equal Least Significant (LS) bits. In Asiacrypt '98, Boneh, Durfee and Frankel (BDF) described several interesting 'partial key exposure' attacks on the RSA system. In particular, for low public exponent RSA, they show how to recover in time polynomial in n the whole secret-exponent d given only the n=4 LS bits of d. In this note, we relax a hidden assumption in the running time estimate presented by BDF for this attack. We show that the running time estimated by BDF for their attack is too low for (m- LSbS) RSA moduli by a factor in the order of 2m. Thus the BDF attack is intractable for such moduli with large m. Furthermore, we prove a general related result, namely that if low-exponent RSA using an (m - LSbS) modulus is secure against poly-time conventional attacks, then it is also secure against poly-time partial key exposure attacks accessing up to 2m LS bits of d. Therefore, if low-exponent RSA using (n=4(1 - ?) - LSbS) moduli for small ? is secure, then this result (together with BDF's result on securely leaking the n=2 MS bits of d) opens the possibility of fast and secure public-server-aided RSA decryption/signature generation.
13603559
A new metric based on extended spatial frequency and its application to DWT based fusion algorithms
A new quantitative metric is proposed to objectively evaluate the quality of fused imagery. The measured value of the proposed metric is used as feedback to a fusion algorithm such that the image quality of the fused image can potentially be improved. This new metric, called the ratio of spatial frequency error (rSFe), is derived from the definition of a previous measure termed ''spatial frequency'' (SF) that reflects local intensity variation. In this work, (1) the concept of SF is first extended by adding two diagonal SFs, then, (2) a reference SF (SF"R) is computed from the input images, and finally, (3) the error SF (SF"E) (subtracting the fusion SF from the reference SF), or the ratio of SF error (rSFe=SF"E/SF"R), is used as a fusion quality metric. The rSFe (which can be positive or negative) indicates the direction of fusion error-over-fused (if rSFe>0) or under-fused (if rSFe<0). Thus, the rSFe value can be back propagated to the fusion algorithm (BP fusion), thereby directing further parameter adjustments in order to achieve a better-fused image. The accuracy of the rSFe is verified with other quantitative measurements such as the root mean square error (RMSE) and the image quality index (IQI), as well as with a qualitative perceptual evaluation based on a standard psychophysical paradigm. An advanced wavelet transform (aDWT) method that incorporates principal component analysis (PCA) and morphological processing into a regular DWT fusion algorithm is implemented with two adjustable parameters-the number of levels of DWT decompositions and the length of the selected wavelet. Results with aDWT were compared to those with a regular DWT and with a Laplacian pyramid. After analyzing several inhomogeneous image groups, experimental results showed that the proposed metric, rSFe, is consistent with RMSE and IQI, and is especially powerful and efficient for realizing the iterative BP fusion in order to achieve a better image quality. Human perceptual assessment was measured and found to strongly support the assertion that the aDWT offers a significant improvement over the DWT and pyramid methods.
3234900
On Algebraic Immunity and Annihilators
Algebraic immunity AI(f) defined for a boolean function f measures the resistance of the function against algebraic attacks. Currently known algorithms for computing the optimal annihilator of f and AI(f) are inefficient. This work consists of two parts. In the first part, we extend the concept of algebraic immunity. In particular, we argue that a function f may be replaced by another boolean function fc called the algebraic complement of f. This motivates us to examine AI(fc). We define the extended algebraic immunity of f as AI*(f)= min {AI(f), AI(fc)}. We prove that 0≤AI(f)–AI*(f)≤1. Since AI(f)–AI*(f)= 1 holds for a large number of cases, the difference between AI(f) and AI*(f) cannot be ignored in algebraic attacks. In the second part, we link boolean functions to hypergraphs so that we can apply known results in hypergraph theory to boolean functions. This not only allows us to find annihilators in a fast and simple way but also provides a good estimation of the upper bound on AI*(f).