Sparse representation-based visual tracking approaches have attracted increasing interests in the community in recent years. The main idea is to linearly represent each target candidate using a set ...of target and trivial templates, while imposing a sparsity constraint onto the representation coefficients. After we obtain the coefficients using ℓ 1 -norm minimization methods, the candidate with the lowest error, when it is reconstructed using only the target templates and the associated coefficients, is considered as the tracking result. In spite of promising system performance widely reported, it is unclear if the performance of these trackers can be maximized. In addition, computational complexity caused by the dimensionality of the feature space limits these algorithms in real-time applications. In this paper, we propose a real-time visual tracking method based on structurally random projection (RP) and weighted least squares (WLS) techniques. In particular, to enhance the discriminative capability of the tracker, we introduce background templates to the linear representation framework. To handle appearance variations over time, we relax the sparsity constraint using a WLS method to obtain the representation coefficients. To further reduce the computational complexity, structurally RP is used to reduce the dimensionality of the feature space, while preserving the pairwise distances between the data points in the feature space. Experimental results show that the proposed approach outperforms several state-of-the-art tracking methods.
The focus of this Letter is on the development of a new effective approach for the hardware implementation of Volterra filters. The proposed approach is based on exploiting the different significance ...levels of the branches in a reduced-rank Volterra implementation aiming to reduce the complexity required for implementing each branch. In this Letter, the probability of overflow is used as a metric to define individual word lengths for the fixed-point implementation of each branch. Experimental results corroborate the capability of the proposed approach for obtaining precise implementations with considerable reduction in computational complexity.
This paper tackles the controllability problem of Boolean control networks (BCNs). By resorting to the semi-tensor product technique and the Warshall algorithm, several improved novel reachability ...and controllability criteria are obtained for the BCNs. Through constructing a sequence of rigorous Boolean matrices, controllability matrix of the considered BCNs is derived iteratively. It is worth pointing out that the proposed method has lower computational complexity, and thus facilitates the reachability and controllability analysis for BCNs. In addition, the issue concerning controllability of BCNs with undesirable interior states is investigated by checking a set of designated Boolean matrices. Finally, to test the effectiveness of the obtained theoretical results, a genetic network model known as the λ switch is used as an example for numerical simulation.
We propose a new method for reconstruction of sparse signals with and without noisy perturbations, termed the subspace pursuit algorithm. The algorithm has two important characteristics: low ...computational complexity, comparable to that of orthogonal matching pursuit techniques when applied to very sparse signals, and reconstruction accuracy of the same order as that of linear programming (LP) optimization methods. The presented analysis shows that in the noiseless setting, the proposed algorithm can exactly reconstruct arbitrary sparse signals provided that the sensing matrix satisfies the restricted isometry property with a constant parameter. In the noisy setting and in the case that the signal is not exactly sparse, it can be shown that the mean-squared error of the reconstruction is upper-bounded by constant multiples of the measurement and signal perturbation energies.
Cuckoo search (CS) algorithm, based on the brood parasitic behaviour of cuckoo species, since its inception, has proved its worth in various fields of research and can be considered as an efficient ...problem solver. Though CS is a very good algorithm, its performance degrades as the problem complexity increases. So a new version namely self-adaptive CS (SACS) is proposed to improve its performance. The algorithm employs adaptive parameters and hence no parameter tuning is required to be done. Here proportional population reduction based on the fitness of current best and previous best solution is followed. Secondly, in order to improve the exploration and exploitation tendencies, the Gaussian sampling mechanism known as bare-bones variant along with division of population and generations is added. The concept of Weibull distributed probability switching is also added to increase the balance between the exploration and exploitation processes. Further, CS as an extension of differential evolution (DE), genetic algorithm (GA), stability analysis with respect to Von Neumann’s stability criteria are also presented. For performance evaluation, the SACS algorithm is tested on CEC 2017 benchmark problems and compared with respect to self-adaptive DE (SaDE), JADE, success-history based adaptive DE (SHADE), SHADE with linear population size reduction (LSHADE), mean-variance mapping optimization (MVMO), cuckoo version 1.0 (CV1.0), cuckoo version new (CVnew) and others. Experimental results and statistical analysis show that the proposed SACS algorithm performs better than SaDE, JADE, CV1.0, CVnew and CS whereas comparable with respect to LSHADE, SHADE, and MVMO. Convergence profiles further validate the results.
Watershed is a widespread technique for image segmentation. Many researchers apply the method implemented in open source libraries without a deep understanding of its characteristics and limitations. ...In the review, we describe benchmarking outcomes of six open-source marker-controlled watershed implementations for the segmentation of 2D and 3D images. Even though the considered solutions are based on the same algorithm by flooding having O(n)computational complexity, these implementations have significantly different performance. In addition, building of watershed lines grows processing time. High memory consumption is one more bottleneck for dealing with huge volumetric images. Sometimes, the usage of more optimal software is capable of mitigating the issues with the long processing time and insufficient memory space. We assume parallel processing is capable of overcoming the current limitations. However, the development of concurrent approaches for the watershed segmentation remains a challenging problem.
Effectively determining the accurate locations of sensor nodes while preserving data privacy is an interesting and challenging problem in the research of wireless sensor networks. On the basis of the ...well-performing distributed iterative localization framework in wireless sensor networks, this article proposes a dual privacy-preserving scheme based on node-intermittent updates and noises injection. A comprehensive analysis of the localization algorithm in terms of convergence and privacy-preserving performance is presented. It is theoretically demonstrated that the localization algorithm can achieve global accurate localization without leaking the privacy information of sensor nodes. At last, the performance of the privacy-preserving localization algorithm is verified by building an experimental platform containing six robots.
AntMan Weng, Chenkai; Yang, Kang; Yang, Zhaomin ...
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security,
11/2022
Conference Proceeding
Recent works on interactive zero-knowledge (ZK) protocols provide a new paradigm with high efficiency and scalability. However, these protocols suffer from high communication overhead, often linear ...to the circuit size. In this paper, we proposed two new ZK protocols with communication sublinear to the circuit size, while maintaining a similar level of computational efficiency. (1) We designed a ZK protocol that can prove B executions of any circuit C in communication O(B + |C|) field elements (with free addition gates), while the best prior work requires a communication of O(B|C|) field elements. Our protocol is enabled by a new tool called as information-theoretic polynomial authentication code, which may be of independent interest. (2) We developed an optimized implementation of this protocol which shows high practicality. For example, with B=2048, |C|=221, and under 50 Mbps bandwidth and 16 threads, QuickSilver, a state-of-the-art ZK protocol based on vector oblivious linear evaluation (VOLE), can only prove 0.71 million MULT gates per second (mgps) and send one field element per gate; our protocol can prove 15.74 mgps (22x improvement) and send 0.0061 field elements per gate (164x improvement) under the same hardware configuration. (3) Extending the above idea, we constructed a ZK protocol that can prove a single execution of any circuit C in communication O(|C|3/4). This is the first ZK protocol with sublinear communication for an arbitrary circuit in the VOLE-based ZK family.
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