waashk/dblp huggingface dataset:
computer vision - accv 2007, 8th asian conference on computer vision, tokyo, japan, november 18-22, 2007, proceedings, part ii we address the problem of bandwidth selection in mls surfaces. while the problem has received relatively little attention in the literature, we show that appropriate selection plays a critical role in the quality of reconstructed surfaces. we formulate the mls polynomial fitting step as a kernel regression problem for both noiseless and noisy data. based on this framework, we develop fast algorithms to find optimal bandwidths for a large class of weight functions. we show experimental comparisons of our method, which outperforms heuristically chosen functions and weights previously proposed. we conclude with a discussion of the implications of the levin's two-step mls projection for bandwidth selection.
robust 3d face recognition based on rejection and adaptive region selection. in this paper, we propose an effective fingerprint matching algorithm based on ridge count matching and minutiae subset combination. in the algorithm, the orientation-based ridge patterns are first utilized to remove the spuriously matched minutiae pairs. then the reliable ridge counts between every two minutiae are estimated to improve the minutiae relationship, and finally the matched minutiae subsets corresponding to different alignments are selectively combined to reduce the influence caused by distortions in fingerprints. experimental results on nist-4 show that our method achieves a much better matching performance
gradient vector flow over manifold for active contours. in this paper, we propose a moving object extraction technique for mpeg coded data directly. it is a change-based motion object extraction approach, which discriminates background and moving objects by means of the higher-order statistics (hos) performed on the interframe differences of dc image. the dc image is partly decoded picture from the compressed video for the rapid reconstruction of image data. in order to employ an optimal threshold in moving object detection stage, the background is detected by the moment-preserving thresholding technique for each frame. based on the background statistic, the proportion of background variance is employed to extract the final object mask by comparison with the fourth moment measure and the variance. experimental results have demonstrated that the proposed approach worked efficiently and showed a robust result for object extraction in compressed video.
learning logic rules for scene interpretation based on markov logic networks. artificial intelligence technique namely artificial neural network (ann) was used to describe the enzymatic kinetics of cellulose hydrolysis in a heterogeneous system, and compared with response surface methodology (rsm). three hydrolysis conditions (activity of added cellulase, substrate concentration and time) served as the input of the neural network model, and the glucose content served as the output. the experimental data from box-behnken design were used to train the neural network using the back propagation algorithm. the others of 33 design were used to check the performance of the trained network. the ann modelled and predicted values showed better agreement with the experimentally reported ones than rsm. ann could mimic the heterogeneous enzymatic hydrolysis of cellulose.
a statistical-structural constraint model for cartoon face wrinkle representation and generation. canetti, goldreich, goldwasser, and micali (stoc 2000) introduced the notion of resettable zero-knowledge proofs, where the protocol must be zero-knowledge even if a cheating verifier can reset the prover and have several interactions in which the prover uses the same random tape. soon afterwards, barak, goldreich, goldwasser, and lindell (focs 2001) studied the closely related notion of resettable soundness, where the soundness condition of the protocol must hold even if the cheating prover can reset the verifier to have multiple interactions with the same verifier's random tape. the main problem left open by this work was whether it is possible to have a single protocol that is simultaneously resettable zero knowledge and resettably sound. we resolve this question by constructing such a protocol. at the heart of our construction is a new non-black-box simulation strategy, which we believe to be of independent interest. this new strategy allows for simulators which "marry'' recursive rewinding techniques (common in the context of concurrent simulation) with non-black-box simulation. previous non-black-box strategies led to exponential blowups in computational complexity in such circumstances, which our new strategy is able to avoid.
human action recognition using pyramid vocabulary tree. a new block detection receiver is presented for noncoherent orthogonal cdma (such as the cdma is-95a reverse link). this new receiver uses multiple hadamard (or walsh) codes for joint detection instead of using a single walsh code as conventional receivers do. the simulation results show that the new block detection receiver is significantly better than the conventional non-block detection receivers in both additive white gaussian noise and flat rayleigh fading channels. a reduced-complexity algorithm for the block detection is also presented with significant complexity reduction and negligible performance degradation
perception-based lighting adjustment of image sequences. one of the main problems that arises when using gene expression programming (gep) conditions in learning classifier systems is the increasing number of symbols present as the problem size grows. when doing model-building lcs, this issue limits the scalability of such a technique, due to the cost required. this paper proposes a binary representation of gep chromosomes to palliate the computation requirements needed. a theoretical reasoning behind the proposed representation is provided, along with empirical validation.
scalable image retrieval based on feature forest. raid storage systems using scsi and traditional disk drives cannot meet the growing demand of new i/o intensive applications. new technologies such as smart disks and ssa are being proposed to improve the performance, scalability, and reliability of raid systems. the objective of this work is to investigate the impact of smart disks and ssa's spatial reuse property on the performance of raid-5 storage systems. in order to perform this work, we have enhanced cmu's raidframe simulator so that it accurately models the overhead of current scsi and ssa protocols, and we have created smart disk models which include on-drive xor logic and on-drive caches. we observe that neither smart disks alone nor spatial reuse property alone has much impact on raid system performance. however, if smart disks and spatial reuse property are properly used in combination, raid-5 system performance and scalability can be further enhanced. in particular, we propose a parity caching approach to improve the performance of small writes
an effective segmentation for noise-based image verification using gamma mixture models. with the wide adoption of open grid services architecture (ogsa) and web services resource framework (wsrf), the grid is emerging as a service-oriented computing infrastructure for engineers and scientists to solve data and computationally intensive problems. it is envisioned that computing resources in a future grid environment will be exposed as services. service discovery becomes an issue of vital importance for a wider uptake of the grid. this paper presents rssm, a rough sets based service matchmaking algorithm for service discovery with an aim to tolerate uncertainty in identifying service properties. the evaluation results show that the rssm algorithm is more effective in service discovery compared with other mechanisms such as uddi and owls.
color correction and compression for multi-view video using h.264 features. the metal implants have been widely used for the human skeleton in dental, maxillofacial and orthopedic treatments for many years. the main function of the implant is to reinforce the fractured bone or provide a direct attachment for a prosthetic limb. the mechanical based orthopedic fixation normally uses a self-tapping implant to provide connectivity between fractured bones. in such a system, the integration between bone and implant is normally based on a biology process called osseointegration. however, the implantation process courses temperature elevation at the bone-implant interface. clinically the high interfacial temperature affects regeneration of bone tissue and ultimately the osseointegration between implant and bone. in order to investigate the temperature elevation at the bone-implant interface, the authors developed a designated instrument system and special self-tapping implant with k type thermocouples placed close to the outer surface inside the implant. the experiments were carried out using re-hydrated human femurs while the implant was screwed into the femur. in this study, the temperature elevation was investigated using different implant diameters, insertion distances and speeds. the experiments were performed at the operation room temperature 21degc and the recorded peak temperature was 47.2degc. the result showed that there was a considerable temperature increase at the bone-implant interface while a self-tapping implant was inserted.
refined exponential filter with applications to image restoration and interpolation. today's communication-based applications are mostly crafted in a stovepipe development paradigm, which is inflexible to be used by various domain-specific applications and costly in the development phase. in a previous paper, we proposed a new design called cvm (communication virtual machine) to overcome these problems by having a high-level api which can be reused and extended easily for user-centric applications in any domain. within cvm framework, we came across a practical issue, which is actually the case for any end- to-end multimedia communication, namely the nat-traversal (network address translation) problem that limits the reliability and availability of cvm and variants of cvm. in this paper, we explain about the necessity of self-configuration for the nat-traversal problem in end-to-end communications, and propose a solution within the core cvm framework.
a scalable algorithm for learning a mahalanobis distance metric. the results of simulating past and future mass balances suggest that the bering glacier will lose significant ice mass and that the hubbard glacier will grow more slowly in the near future than in the recent past
co-occurrence random forests for object localization and classification. proposed for mpcs, rdt has already been proved to support better performances than most of the direct network, such as smaller diameter based on its vector routing algorithm, smaller degree, embedded mesh/torus topology, etc. it gives a network form method to form groups of networks with recursively structured torus/torus-like networks. a rdt structure can be formed with the method and its related parameters. after analyzing its performance by the average distance, the descending vector routing reducing redundant computations and the fault-tolerant routing algorithm are proposed. a simpler structure named rdt(2,2,1)/a are proposed for the parallel systems with no more than 5000 nodes and given its performance evaluation. considering the structure features of the practical rdts, they are suitable for the interconnection network of an noc design. the design of laying out rdt(2,2, 1)/a is proposed and proved to be available
beyond pairwise shape similarity analysis. it is known that the execution of programs exhibits repetitive phases; in other words, the execution of programs can be partitioned into segments of execution, during which the application exhibits unique architectural properties. this property has been used for various optimization goals. in addition, phase information is utilized to reduce the run time of the architectural simulation. conventionally, an application is examined in an architecture-independent manner (such as the number of times a basic block is executed) to extract information about the phases and then only the representative execution intervals are executed to analyze architectural choices. we claim that such approaches are becoming inadequate in the many-core era as application execution is not dominated by the instructions only, but instead the communication structure of the application is becoming as important as the instruction behavior. hence, we propose to utilize communication behavior to determine the phases of an application. our results reveal that the inclusion of the communication information can increase the accuracy of the phase detection significantly. specifically, for splash2 and mine-bench applications, the average (geometric mean) cpi error rate with the instruction-based phase detection is 11.01%, while our phase detection scheme has an average error rate of 3.41% when compared to the simulations that run the applications to completion.
computer vision - accv 2009, 9th asian conference on computer vision, xi'an, china, september 23-27, 2009, revised selected papers, part i in this paper we propose an individualized 3d facial model constructed from the anatomical perspective for realistic facial expression synthesis. our model incorporates a physically-based approximation to facial skin tissue, a set of anatomically-motivated facial muscle actuators and underlying skull structure. the skin is modeled as a multi-layer mass-spring lattice by taking into account the nonlinear stress-strain relationship of the real skin. the 3d face model incorporates a skull structure which extends the scope of facial motion and facilitates facial muscle definition. the automatic facial muscle construction is achieved by using an efficient muscle mapping approach that ensures different muscles to be located at the anatomically correct positions between the skin and skull layers. for computational efficiency, we devise a semi-implicit integration method to numerically solve the governing dynamics. the dynamic facial animation algorithm runs at an interactive rate with realistic facial expressions to be synthesized.
an improved template matching method for object detection. digital documents are easily copied and distributed ille- gally. document copy detection is a powerful tool to pro- tect the author's intellectual property and to improve the efficiency of information retrieval. it is difficult for the ex- isting copy detection systems to identify the sentence struc- ture changed copies. to address the problem, we research the semantic level of natural language processing and pro- pose a document copy detection method based on chinese semantic knowledge. we introduce the realization mecha- nisms of chinese language analysis, which contains syn- tactic parsing and semantic analyzing. we also report on the experimental comparison the proposed method with the representative document copy detection systems. the result is satisfying.
gait recognition using procrustes shape analysis and shape context. wireless sensor networks (wsns) deployed for mission-critical applications face the fundamental challenge of meeting stringent spatiotemporal performance requirements using nodes with limited sensing capacity. although advance network planning and dense node deployment may initially achieve the required performance, they often fail to adapt to the unpredictability of physical reality. this paper explores efficient use of mobile sensors to address the limitations of static wsns in target detection. we propose a data fusion model that enables static and mobile sensors to effectively collaborate in target detection. an optimal sensor movement scheduling algorithm is developed to minimize the total moving distance of sensors while achieving a set of spatiotemporal performance requirements including high detection probability, low system false alarm rate and bounded detection delay. the effectiveness of our approach is validated by extensive simulations based on real data traces collected by 23 sensor nodes.
computer vision - accv 2009, 9th asian conference on computer vision, xi'an, china, september 23-27, 2009, revised selected papers, part ii the transmission delays in the networked control systems are inevitable and can degrade the system's performance or stability. this paper has proposed an r-suboptimal hinfin controller for networked control systems with model uncertainty and network induced delay which is longer than one sampling period. the closed-loop system with structured uncertainties and long transmission delay is asymptotically stable. simulation is applied to numerical examples with networked control show that the proposed method works well.
finger-vein recognition based on a bank of gabor filters. although fuzzy logic has been successfully applied in many different problem domains, fuzzy solutions typically structure the problem task as one of static categorisation. this may not be appropriate for dynamic systems, especially where higher-order information is unavailable. the paper proposes an approach to reasoning about dynamic systems drawing upon the first-order approach to temporal logic. a brief overview of the classical theory is provided and extended to a fuzzy theory modelling the inherent vagueness of linguistic terms such as "recently". the notion of a temporal qualification is developed as a domain independent method for augmenting base domains and term set of a linguistic variable. such extended variables are termed temporal linguistic variables. the technique is then applied to a simple dynamic system highlighting its advantage over traditional approaches. since temporal linguistic variables are a special case of linguistic variable they are immediately applicable in fuzzy knowledge based system and machine learning contexts
a novel visual organization based on topological perception. with 3d (3-dimensional) movement's ability and rhythmic locomotion mode, a nature snake makes itself survive in rugged terrains. the rhythmic activities of most creatures are generated by the cpg (central pattern generator). based on this fact, the sustained-type neuron has been adopted to construct a cyclic inhibitory cpg model for a snake-like robot whose joints are perpendicularly connected in series. having compared with the sustained-type neuron and the mutual inhibitory cpg, the cyclic inhibitory cpg was proven to generate capably rhythmic output with the least number of differential equations. in this paper, we introduce the neuron network organized by the cyclic inhibitory cpgs connected in line with unilateral excitation to control the 3d locomotion of a snake-like robot, and present the necessary condition for the cpg neuron network to sustain a rhythmic output. by implementing this control architecture to a simulator with consideration of mechanical dynamics of a real snake-like robot "perambulator", preliminary parameter setting of the cpg neuron network for its 3d locomotion is obtained. moreover, it is shown that "perambulator" can successfully exhibit 3d locomotion by using the output of the proposed cpg network. the obtained results have also provided a bran new approach to understand the unknown neuron network of nature snakes
head pose estimation based on manifold embedding and distance metric learning. this paper proposes a visual cognitive neural network for automatic object searching and locating. the model consists of two sub-networks. one is a visual perceiving network, which simulates human eyes to input image signals and recognize an object's direction and distance in terms of a high-level perceiving neuron's maximum response. the other one is an eyeball-motion controlling network, which simulates that human brain's high-level perceiving neurons transfer their responses to eyeball-motion controlling muscle cells to change eye's gaze to the position of the object that the perceiving system is attentive to or interested in. the system is applied to human face features searching and experiments show a promising result.
an online framework for learning novel concepts over multiple cues. in this paper, a discriminative manifold learning method for face recognition is proposed which achieved the discriminative embedding the high dimensional face data into a low dimensional hidden manifold. unlike the recently proposed lle, isomap and eigenmap algorithms, which are based on reconstruction purpose, our method uses the rca algorithm to achieve nonlinear embedding and data discrimination at the same time. also, the lle and isomap algorithms are crucially depends on the appropriateness of the neighborhood construction rule, in this paper, a ck-nearest neighborhood rule is proposed to achieve better neighborhood construction. experimental results indicate the promising performance of the proposed method.
evolving mean shift with adaptive bandwidth: a fast and noise robust approach. subspace clustering is one of the best approaches for discovering meaningful clusters in high dimensional space. one cluster in high dimensional space may be transcribed into multiple distinct maximal clusters by projecting onto different subspaces. a direct consequence of clustering independently in each subspace is an overwhelmingly large set of overlapping clusters which may be significantly similar. to reveal the true underlying clusters, we propose a similarity measurement of the overlapping clusters. we adopt the model of gaussian tailed hyper-rectangles to capture the distribution of any subspace cluster. a set of experiments on a synthetic dataset demonstrates the effectiveness of our approach. application to real gene expression data also reveals impressive meta-clusters expected by biologists.
visual saliency based on conditional entropy. this paper analyses the defect of the designing model of load balancing in hybrid p2p network, and proposes a new strategy of scheduling for load balancing, which based on culture algorithm of multilayer belief spaces. according to the current load status of each super-node in the system, it can calculate its load weight of the next time section by using the cultural algorithm, and assign the current requests of login with weighted round-robin. the extracted knowledge which is got by selecting the best belief space from the multilayer belief space is used to optimize the constrains of the evolutionary, in order to accelerate the optimization process of the calculation of load weight. simulation experiments show that the allocation of login request to each node is to be balance much faster through using of cultural algorithm based on multilayer belief spaces.
image-set based face recognition using boosted global and local principal angles. semantics-preserving dimensionality reduction refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encountered in many areas such as machine learning, pattern recognition, and signal processing. this has found successful application in tasks that involve data sets containing huge numbers of features (in the order of tens of thousands), which would be impossible to process further. recent examples include text processing and web content classification. one of the many successful applications of rough set theory has been to this feature selection area. this paper reviews those techniques that preserve the underlying semantics of the data, using crisp and fuzzy rough set-based methodologies. several approaches to feature selection based on rough set theory are experimentally compared. additionally, a new area in feature selection, feature grouping, is highlighted and a rough set-based feature grouping technique is detailed.