Robust Object Tracking via Information Theoretic Measures

Object tracking is a very important topic in the field of computer vision.Many sophisticated appearance models have been proposed.Among them,the trackers based on holistic appearance information provide a compact notion of the tracked object and thus are robust to appearance variations under a small amount of noise.However,in practice,the tracked objects are often corrupted by complex noises(e.g.,partial occlusions,illumination variations)so that the original appearance-based trackers become less effective.This paper presents a correntropy-based robust holistic tracking algorithm to deal with various noises.Then,a half-quadratic algorithm is carefully employed to minimize the correntropy-based objective function.Based on the proposed information theoretic algorithm,we design a simple and effective template update scheme for object tracking.Experimental results on publicly available videos demonstrate that the proposed tracker outperforms other popular tracking algorithms.

A K-means clustering based blind multiband spectrum sensing algorithm for cognitive radio

In this paper,a blind multiband spectrum sensing(BMSS)method requiring no knowledge of noise power,primary signal and wireless channel is proposed based on the K-means clustering(KMC).In this approach,the KMC algorithm is used to identify the occupied subband set(OSS)and the idle subband set(ISS),and then the location and number information of the occupied channels are obtained according to the elements in the OSS.Compared with the classical BMSS methods based on the information theoretic criteria(ITC),the new method shows more excellent performance especially in the low signal-to-noise ratio(SNR)and the small sampling number scenarios,and more robust detection performance in noise uncertainty or unequal noise variance applications.Meanwhile,the new method performs more stablely than the ITC-based methods when the occupied subband number increases or the primary signals suffer multi-path fading.Simulation result verifies the effectiveness of the proposed method.

对潜在信息资源的认识研究

Based on a description of the implication,character and type of information resources,this article analyzes the potential information resourecs which are seldom noticed by people.Emphases are put on their specific properties.The necessity and urgency of developing potential information resources are elaborated.The possibility of developing and utilizing potential information resources are predicted.

Seismic wavelet estimation via a system identification method

On the assumption that the wavelet is causal and nonminimum phase, an autoregressive moving average （ARMA） model is introduced to fit the seismic trace. Seismic wavelet extraction is converted to parameters estimation of the ARMA model. Singular value decomposition （SVD） of an appropriate matrix formed by autocorrelation is exploited to determine the autoregressive （AR） order, and the cumulant-based SVD-TLS （total least squares） approach is proposed to obtain the AR parameters. The author proposes a new moving average （MA） model order determination method via combining the information theoretic criteria method and higher-order cumulant method. The cumulant approach is used to achieve the MA parameters. Theoretical analysis and numerical simulations demonstrate the feasibility of the wavelet extraction approach.

Method for determining number of coherent signals in the presence of colored noise

The approach of estimating the number of signals based on information theoretic criteria has good performance in the assumption of white noise, but it always leads to false estimation of the coherent sources in colored noise. An approach combining the combined information theoretic criteria and eigen- value correction, is presented to determine number of signals. The method uses maximum likelihood （ML） and information theoretic criteria to estimate coherent signals alternately, then eliminate the inequality of the eigenvalues caused by colored noise by correcting the noise eigenvalues. The computer simulation results prove the effective performance of the method.

On Construction of Optimal A^2-Codes

Two authentication codes with arbitration (A 2 codes) are constructed from finite affine spaces to illustrate for the first time that the information theoretic lower bounds for A 2 codes can be strictly tighter than the combinatorial ones. The codes also illustrate that the conditional combinatorial lower bounds on numbers of encodingdecoding rules are not genuine ones. As an analogue of 3 dimensional case, an A 2 code from 4 dimensional finite projective spaces is constructed, which meets both the information theoretic and combinatorial lower bounds.

Unconditionally Secure Oblivious Polynomial Evaluation:A Survey and New Results

Oblivious polynomial evaluation(OPE)is a two-party protocol that allows a receiver,R to learn an evaluation f(α),of a sender,S's polynomial(f(x)),whilst keeping both a and f(x)private.This protocol has attracted a lot of attention recently,as it has wide ranging applications in the field of cryptography.In this article we review some of these applications and,additionally,take an in-depth look at the special case of information theoretic OPE.Specifically,we provide a current and critical review of the existing information theoretic OPE protocols in the literature.We divide these protocols into two distinct cases(three-party and distributed OPE)allowing for the easy distinction and classification of future information theoretic OPE protocols.In addition to this work,we also develop several modifications and extensions to existing schemes,resulting in increased security,flexibility and efficiency.Lastly,we also identify a security flaw in a previously published OPE scheme.