waashk/dblp huggingface dataset:
face recognition by estimating facial distinctive information distribution. the analysis shows that the conventional codebook construction of grassmannian subspace packing can not control the performance loss caused by a linear receiver, while a proper unitary perturbation to the codebook is capable of compensating for this performance loss. this paper therefore proposes a novel hierarchical codebook to exploit the gain of unitary perturbation. the hierarchical codebook consists of a grassmannian subcodebook and a proposed perturbation subcodebook. to implement precoding, this paper also presents a successive codeword selection scheme, thus the receiver would successively selects two preferred codewords from grassmannian and perturbation subcodebooks. with the feedback binary indices of these selections, the transmitter uses the product of two preferred codewords as the precoder. the theoretical analysis of the proposed precoding technique shows that the usage of the perturbation subcodebook can improve to a certain degree the system performance in terms of throughput as well as ber, with a small additional feedback overhead, and the proposed codebook would reduce the computational and storage requirements in contrast to the conventional codebook. it is also shown via computer simulations that the proposed technique gives a better ber performance than the single grassmannian codebook based precoding technique does, even if the feedback overhead remains the same.
image content based curve matching using hmcd descriptor. a proportion factor is constructed though the maximum aposteriori probability of examples in test data to select the training examples in incremental learning process. instead of complex normal classify loss expression, the proportion factor lambda is used to estimate the classify loss to improve classification efficiency. the final experiment shows that this algorithm is feasible, and more accurate than simple bayesian classifier. the computing time is highly reduced on the optimal selection of examples in incremental learning process.
non-rigid shape matching using geometry and photometry. zhou wang proposed the structural similarity theory (mssim), guan-hao chen proposed a marginal texture distorts theory on it. jian-xin pang proposed a method of image quality assessment based on the energy of structural distortion (esd). because the theory isn't applied directly on the video field and it don't think over hvs. so we propose a method of video quality assessment based on the sensitive region. first of all, we get the energy of structural distortion (esd)based on the block. then, we get the weighted factor according to the structure information and the movement information. finally, we get the final results according to the hvs. from the last results, we know that the weighting method base on the esd (wesd) is better than the psnr, mssim and essim on the compression loss, smooth loss and noise loss.
model-based 3d object localization using occluding contours. chinese remainder theorem based rsa (crt-rsa) digital signature has important applications in smart cards. previous crt-rsa algorithms such as crt-2 and bos are susceptible to practical hardware fault attacks. in this paper, a new crt-rsa algorithm with countermeasures to hardware fault attacks is proposed. to our knowledge, the proposed algorithm is the first that can resist what we call the single-fault adversarial attacks. the proposed algorithm first computes the signature using crt in a secret algebraic setting, then a set of fault-detection variables are computed to detect possible faults. lastly, the signature is mapped from the secret algebraic setting to the intended setting. by using a random number and the fault detection variables, every step of the algorithm is protected from hardware faults. the output of the algorithm will be fully randomized in case of faults. the crt's speed advantages are also maintained. the proposed algorithm is approximately two times as fast as the direct form rsa for the two-prime case, and about four times as fast for the three-prime case
convolutional virtual electric field external force for active contours. in this paper, a novel approach is proposed for estimating traffic matrices. our method, called pamtram for partial measurement of traffic matrices, couples lightweight origin-destination (od) flow measurements along with a computationally lightweight algorithm for producing od estimates. the first key aspect of our method is to actively select a small number of informative od flows to measure in each estimation interval. to avoid the heavy computation of optimal selection, we use intuition from game theory to develop randomized selection rules, with the goals of reducing errors and adapting to traffic changes. we show that it is sufficient to measure only one flow per measurement period to drastically reduce errors-thus rendering our method lightweight in terms of measurement overhead. the second key aspect is an explanation and proof that an iterative proportional fitting algorithm approximates traffic matrix estimates when the goal is a minimum mean-squared error; this makes our method lightweight in terms of computation overhead. a one-step error bound is provided for pamtram that bounds the average error for the worst scenario. we validate our method using data from sprint's european tier-1 ip backbone network and demonstrate its consistent improvement over previous methods.
solving multilabel mrfs using incremental -expansion on the gpus. video comprises multiple types of textual, audio and visual information, and each of them contains abundant semantic information. therefore multimodal features query and fusion are necessary in video retrieval. in this paper, we propose a new video retrieval model, which adopts multi-model including text, image, semantic concept and camera motion to query video. then relation algebra expression is advanced to fuse multimodal information instead of traditional linear fusion method. in semantic concept detection model, bayesian network based ontology is proposed to extract concepts. the experiments on trecvid 2005 corpus have demonstrated a superior performance compared with exiting key approaches of video retrieval by multimodal information fusion.
image search result summarization with informative priors. this paper is motivated to improve the performance of individual ensembles using a hybrid mechanism in the regression setting. based on an error-ambiguity decomposition, we formally analyze the optimal linear combination of two base ensembles, which is then extended to multiple individual ensembles via pairwise combinations. the cocktail ensemble approach is proposed based on this analysis. experiments over a broad range of data sets show that the proposed approach outperforms the individual ensembles, two other methods of ensemble combination, and two state-of-the-art regression approaches.
globally optimal spatio-temporal reconstruction from cluttered videos. offshore outsourcing has become popular because of cost or skill advantage. china is considered as one of major global software and information service offshore destinations, but it cannot compete with india right now. based on literature review, this paper first presents an overview of the industry. then 38 service providers in china are investigated to give a firm-level analysis of the industry. a framework of factors influencing the industry is presented. influence factors are classified into macro factors, middle factors, and micro factors, each of which is analyzed in detail. it is concluded that china software and information service offshore outsourcing industry is of great potential, but needs marketing and advertising.
exploiting intensity inhomogeneity to extract textured objects from natural scenes. in large scale mobile gaming environments, efficient mechanisms for state update is crucial to allow graceful real-time interaction of a large number of players, under limited wireless network bandwidth. by using the state updating threshold as a key parameter that bridges the resulting state inconsistency (or distortion) and the network traffic, we are able to model the fundamental traffic-distortion tradeoffs. given the tradeoffs for all users, an optimal bandwidth allocation can be derived using well-known convex programming techniques. by exploring the temporal locality of gaming behavior, we also propose a prediction method to realize on-line bandwidth adaptation. using real data trace from a multi-player driving game, the proposed network aware bandwidth allocation method, naba, is able to achieve significant reduction in state distortion compared to two baselines: uniform and proportional policies. naba is also adaptable to variations in system parameters, including bandwidth constraint and network delay.
object detection with multiple motion models. presents a method of generating test sequences for concurrent programs and communication protocols that are modeled as communicating nondeterministic finite-state machines (cnfsms). a conformance relation, called trace-equivalence, is defined within this model, serving as a guide to test generation. a test generation method for a single nondeterministic finite-state machine (nfsm) is developed, which is an improved and generalized version of the wp-method that generates test sequences only for deterministic finite-state machines. it is applicable to both nondeterministic and deterministic finite-state machines. when applied to deterministic finite-state machines, it yields usually smaller test suites with full fault coverage than the existing methods that also provide full fault coverage, provided that the number of states in implementation nfsms are bounded by a known integer. for a system of cnfsms, the test sequences are generated in the following manner: a system of cnfsms is first reduced into a single nfsm by reachability analysis; then the test sequences are generated from the resulting nfsm using the generalized wp-method
unfolding a face: from singular to manifold. static timing analysis safely bounds worst-case execution times to determine if tasks can meet their deadlines in hard real-time systems. however, conventional timing analysis requires that the upper bound of loops be known statically, which limits its applicability. parametric timing analysis methods remove this constraint by providing the wcet as a formula parameterized on loop bounds. this paper contributes a novel technique to allow parametric timing analysis to interact with dynamic real-time schedulers. by dynamically detecting actual loop bounds, a lower wcet bound can be calculated, on-the-fly, for the remaining execution of a task. we analyze the benefits from parametric analysis in terms of dynamically discovered slack in a schedule. we then assess the potential for dynamic power conservation by exploiting parametric loop bounds for parascale, our intra-task dynamic voltage scaling (dvs) approach. our results demonstrate that the parametric approach to timing analysis provides 66%-80% additional savings in power consumption. we further show that using this approach combined with online intra-task dvs to exploit parametric execution times results in much lower power consumption. hence, even in the absence of dynamic scheduling, significant savings in power can be obtained, e.g., in the case of cyclic executives
gender from body: a biologically-inspired approach with manifold learning. a new feature-based method for the correspondence problem is proposed. the used feature is the boundary of a parameter-dependent connected component ((ε,&delta;)-component, wang and bhattacharya, 1996) of an image. we prove that under certain conditions, there is a one-to-one relationship between the sets of the boundary points in a pair of stereo images. this correspondence may be identified through epipolar geometry. furthermore, since such connected components may represent some meaningful objects (wang and bhattacharya, 1996) in images, we may obtain the corresponding objects directly, instead of only the corresponding points or lines as in some other methods which need the process of feature grouping to conduct further analysis. also, a hierarchy of the connected components provides us with a coarse-to-fine matching method to recover the surface corresponding to a connected component
lorentzian discriminant projection and its applications. with the steady development of wimax based broadband wireless access networks, complete and accurate simulation studies become crucial. in an effort to further improve our ns-2 simulation model for mobile wimax, we have implemented a selective repeat automatic retransmission request (sr-arq) mechanism into our model and evaluated its performance and accuracy. in this paper, we present the design and implementation methodology of the wimax sr-arq simulation model in ns-2 and discuss its accuracy via extensive simulation studies. our evaluation clearly shows that sr-arq achieves increased successful packet delivery ratio and goodput, which is true for both non-saturated channels and saturated channels. in each case a cost of increased bandwidth consumption and latency overhead for received packets is also quantitatively analyzed. we believe the implementation of sr-arq in the ns-2 simulation model and its evaluation studies will provide profound empirical values to wimax field test studies.
gender recognition via locality preserving tensor analysis on face images. mithos (micro-kernel threads operating system) is an experimental operating system for embedded systems. the system kernel is a first implementation of the posix minimal real-time system profile. it is based on prior work of a library implementation of pthreads (posix threads). the system is fully preemptive. it supports multi-threading within a single process environment with shared kernel and user space, i.e. real-time tasks are mapped onto posix threads. it exhibits remarkable timing predictability intended for hard real-time requirements. this is achieved by a careful design of only few device drivers. the system has been implemented and tested on the sparc vme architecture. the system includes a fast context switching algorithm for the sparc which outperforms the context switch under sunos and matches the performance under solaris. it supports selective enabling and disabling of hardware components (mmu, caches, etc.) since its sources are available. furthermore, an implementation-defined extension of posix threads for deadline scheduling is presented. overall, the system exhibits slightly faster performance than sunos 4.x and is considerably more predictable in its timing behavior. applications of the kernel range from evaluating the overhead of new language features in ada 95 and its runtime system, verifying static timing predictions on a bare machine, to providing the operating system for small embedded system that require a high timing predictability
interactive super-resolution through neighbor embedding. this paper proposes a distributed video coding scheme based on the zero tree entropy (zte) coding. wyner-ziv theory on source coding with side information is taken as the basic coding principle, which makes independent encoding and joint decoding possible. in this scheme, wavelet transform is used to exploit the spatial correlation of a wyner-ziv frame. the quantized wavelet coefficients are reorganized in terms of the zero tree structure so as to identify the significant and insignificant coefficients. the significance map is intra-codec and transmitted. in particular, the significant coefficients are independently encoded with turbo coder, and only the parity bits are transmitted. at the decoder, a predictive frame generated through motion-compensated prediction is used as the side information, with which the wyner-ziv frame can be conditionally decoded. experimental results show that, compared to the traditional intra-frame coding and pixel-domain wnyer-ziv video coding, the proposed scheme can achieve a better coding performance, especially at low bit rates
a subjective method for image segmentation evaluation. peer-to-peer media streaming has been an important service on the internet in recent years. the data-driven (or mesh-based) structure is adopted by most working systems,in which data scheduling is one of the important problems.however, those frequently used scheduling algorithms are often faced with such a case: a neighbor peer takes up its bandwidth to deliver the packets that other neighbors can also supply, but some packets only held by it are not delivered.these packets can not be delivered in the current scheduling cycle, even though that the other neighbors have surplus bandwidth. this is a kind of waste of bandwidth and decreases the throughput of transmission. in this paper we propose anew scheduling algorithm aiming at the optimal throughput:bipartite-matching based block scheduling algorithm(bbs).we convert the original data scheduling problem to a problem of finding a maximum match on the correspond bipartite graph, then assign data packets to neighbors according to the maximum match. we evaluate the performance of bbs with extensive experiments and the results show that bbs throughput and provides better streaming quality than those frequently used scheduling algorithms.
polymorphous facial trait code. real-time multicast video distribution is an important component of many multimedia applications. our work addresses the fairness problem in feedback-controlled multicast video distribution systems over best effort networks (such as the internet). we have proposed, implemented and experimented with a scheme called destination set grouping (dsg), where a source maintains a small number of video streams, all carrying the same video but each targeted at receivers with different capabilities. each stream is feedback-controlled within prescribed limits by its group of receivers. receivers may move among groups as their capabilities or the capabilities of the network paths leading to them change. in this paper, we focus on the potential for network overloading caused by the transmission of multiple replicated streams. we propose a number of mechanisms to be implemented at the source and the receivers that can help avert this problem. we also describe an evaluation of these schemes using simulation, and discuss a comparison of replicated-stream versus layered-encoding approaches
adaptive-scale robust estimator using distribution model fitting. in this paper, a method of chinese question classification based on ensemble learning is proposed. words and bi-gram are extracted from question as classic features and feature classifiers are constructed. the classifiers are kinds of simple classifier and their generalization ability are not strong enough, but they are a qualified base learner for ensemble because of their low computational cost, and the generalization feasibility improved with the help of ensemble learning. we translate and modify the uiuc question set and trec2001 question set as chinese question set. experimental results on the corpus show that the proposed method can achieve good performance, the classification precision reaches 87.6%, under the fine grained question types.
human action recognition using non-separable oriented 3d dual-tree complex wavelets. this letter deals with the global exponential synchronization of a class of chaotic networks with time delays. based on the halanay inequality technique and the lyapunov stability theory, the global synchronization of a network about its all variables is derived by only considering the global synchronization of its partial variables, and a delay-independent criteria and decentralized control law is derived to ensure the adaptive exponential synchronization of the model and these results are proved to be able to guarantee different exponential convergence rates for the controlled states and the uncontrolled states of the error systems, respectively, and the simpler, less conservative and more efficient results are easy to be verified in engineering applications. finally, an illustrative example is presented to verify the effectiveness of the presented synchronization scheme.
better correspondence by registration. classification is a major task in the gene sequence analysis. based on the general principle of artificial immune system, this paper first constructed a classifier which inducted antibody-antigen identification, immune colonel reproduction, hypermutation, affinity mature and the network suppression, by simulating how the antigens stimulate the immune network and how the immune network responds. then, a "leave-one-out" method was adopted to test the classifier's performance, applying 1-20th dna sequences of art-model-data with class attribute. its accuracy was up to 90%. at last, a well-pleasing result was got on the prediction of 21-40th dna sequences of art-model-data.
person de-identification in videos. design on the web raises challenging questions concerning how users interact with objects, applications, and other users. in this work, we propose a collaborative and interactive client-server design framework and implement a room design system for our study. we have integrated technologies used in distributed computation (java and corba) and computer graphics (vrml). it divides the design process into three tiers. first, collaborative and interactive design, viewing, and publishing. second, scene generation. third, scene database management. our system can be applied in electronic commerce to improve the existing systems by allowing customers to select furniture and to visualize the whole furnished room in 3d
real-time object detection with adaptive background model and margined sign correlation. as an extensible signaling protocol, sip (session initiation protocol) can be applied in developing video conference system. traditionally, for sip-based centralized video conference system, conferencing scale is limited by both the capability of conference server and the availability of bandwidth. the paper focuses on how to keep conferencing when the number of conference users increases. based on the study of the sip protocol, we analyze the drawback of the existing video conference model, and propose a dynamic scalable service model for sip-based video conference. by this model, the extra service requests can be transferred and served in the cooperated conference servers. the paper presents the conferencing control policy of the model in detail. we developed a prototype of video conference system based on the above model. experimental results show this service model works well.
face recognition via aam and multi-features fusion on riemannian manifolds. rissanen's (1978, 1986, 1989, 1996) minimum description length (mdl) principle is a statistical modeling principle motivated by coding theory. for exponential families we obtain pathwise expansions, to the constant order, of the predictive and mixture codelengths used in mdl. the results are useful for understanding different mdl forms
ultrasound speckle reduction via super resolution and nonlinear diffusion. the digital television (dtv) technology becomes widely available and the need for a good interlace-to-progressive conversion (ipc) algorithm becomes more inevitable. in this paper, a new ipc scheme is proposed, which combines several existing techniques and is suitable for hardware implementation. the proposed scheme consists of three components: a spatial linear pre-filter, a motion estimator, and a three stage adaptive recursive (3sar) filter. the proposed adaptive filter improves the performance of the system without requiring complex hardware design. the computer simulations and real-time fpga/asic implementation demonstrate the efficiency and effectiveness of the proposed scheme in hardware applications