Human tracking in camera network with non-overlapping FOVs

An adaptive human tracking method across spatially separated surveillance cameras with non-overlapping fields of views （FOVs） is proposed. The method relies on the two cues of the human appearance model and spatio-temporal information between cameras. For the human appearance model, an HSV color histogram is extracted from different human body parts （head, torso, and legs）, then a weighted algorithm is used to compute the similarity distance of two people. Finally, a similarity sorting algorithm with two thresholds is exploited to find the correspondence. The spatio- temporal information is established in the learning phase and is updated incrementally according to the latest correspondence. The experimental results prove that the proposed human tracking method is effective without requiring camera calibration and it becomes more accurate over time as new observations are accumulated.

Adaptive topology learning of camera network across non-overlapping views

An adaptive topology learning approach is proposed to learn the topology of a practical camera network in an unsupervised way. The nodes are modeled by the Gaussian mixture model. The connectivity between nodes is judged by their cross-correlation function, which is also used to calculate their transition time distribution. The mutual information of the connected node pair is employed for transition probability calculation. A false link eliminating approach is proposed, along with a topology updating strategy to improve the learned topology. A real monitoring system with five disjoint cameras is built for experiments. Comparative results with traditional methods show that the proposed method is more accurate in topology learning and is more robust to environmental changes.

An Improved Hybrid Genetic Algorithm for Chemical Plant Layout Optimization with Novel Non-overlapping and Toxic Gas Dispersion Constraints

New approaches for facility distribution in chemical plants are proposed including an improved non-overlapping constraint based on projection relationships of facilities and a novel toxic gas dispersion constraint. In consideration of the large number of variables in the plant layout model, our new method can significantly reduce the number of variables with their own projection relationships. Also, as toxic gas dispersion is a usual incident in a chemical plant, a simple approach to describe the gas leakage is proposed, which can clearly represent the constraints of potential emission source and sitting facilities. For solving the plant layout model, an improved genetic algorithm (GA) based on infeasible solution fix technique is proposed, which improves the globe search ability of GA. The case study and experiment show that a better layout plan can be obtained with our method, and the safety factors such as gas dispersion and minimum distances can be well handled in the solution.

A novel non-overlapping approach to accurately represent 2D arbitrary particles for DEM modelling

Mechanical behaviors of granular materials are complicated and greatly influenced by the particle shape.Current,some composite approaches have been proposed for realistic particle shape modelling within discrete element method(DEM),while they cannot give a good representation to the shape and mass properties of a real particle.In this work,a novel algorithm is developed to model an arbitrary particle using a cluster of non-overlapping disks.The algorithm mainly consists of two components:boundary filling and domain filling.In the boundary filling,some disks are placed along the boundary for a precise representation of the particle shape,and some more disks are placed in the domain to give an approximation to the mass properties of the particle in the domain filling.Besides,a simple method is proposed to correct the mass properties of a cluster after domain filling and reduce the number of the disks in a cluster for lower computational load.Moreover,it is another great merit of the algorithm that a cluster generated by the algorithm can be used to simulate the particle breakage because of no overlaps between the disks in a cluster.Finally,several examples are used to show the robust performance of the algorithm.A current FORTRAN version of the algorithm is available by contacting the author.

Adaptive Human Tracking Across Non-overlapping Cameras in Depression Angles

To track human across non-overlapping cameras in depression angles for applications such as multi-airplane visual human tracking and urban multi-camera surveillance,an adaptive human tracking method is proposed,focusing on both feature representation and human tracking mechanism.Feature representation describes individual by using both improved local appearance descriptors and statistical geometric parameters.The improved feature descriptors can be extracted quickly and make the human feature more discriminative.Adaptive human tracking mechanism is based on feature representation and it arranges the human image blobs in field of view into matrix.Primary appearance models are created to include the maximum inter-camera appearance information captured from different visual angles.The persons appeared in camera are first filtered by statistical geometric parameters.Then the one among the filtered persons who has the maximum matching scale with the primary models is determined to be the target person.Subsequently,the image blobs of the target person are used to update and generate new primary appearance models for the next camera,thus being robust to visual angle changes.Experimental results prove the excellence of the feature representation and show the good generalization capability of tracking mechanism as well as its robustness to condition variables.

Parallel Implementation of the Non-Overlapping Template Matching Test Using CUDA

NIST(National Institute of Standards and Technology) statistical test recognized as the most authoritative is widely used in verifying the randomness of binary sequences. The Non-overlapping Template Matching Test as the 7 th test of the NIST Test Suit is remarkably time consuming and the slow performance is one of the major hurdles in the testing process. In this paper, we present an efficient bit-parallel matching algorithm and segmented scan-based strategy for execution on Graphics Processing Unit(GPU) using NVIDIA Compute Unified Device Architecture(CUDA). Experimental results show the significant performance improvement of the parallelized Non-overlapping Template Matching Test, the running speed is 483 times faster than the original NIST implementation without attenuating the test result accuracy.

Boundary Element Method with Non-overlapping Domain Decomposition for Diffusion Equation

A boundary element method based on non-overlapping domain decomposition method to solve the time-dependent diffusion equations is presented. The time-dependent fundamental solution is used in the formulation of boundary integrals and the time integration process always restarts from the initial time condition. The process of replacing the interface values, which needs a summation of boundary integrals related to the boundary values at previous time steps can be treated in parallel iterative procedure. Numerical experiments demonstrate that the implementation of the present algorithm is efficient.

Weber Law Based Approach for Multi-Class Image Forgery Detection

Today’s forensic science introduces a new research area for digital image analysis formultimedia security.So,Image authentication issues have been raised due to the wide use of image manipulation software to obtain an illegitimate benefit or createmisleading publicity by using tempered images.Exiting forgery detectionmethods can classify only one of the most widely used Copy-Move and splicing forgeries.However,an image can contain one or more types of forgeries.This study has proposed a hybridmethod for classifying Copy-Move and splicing images using texture information of images in the spatial domain.Firstly,images are divided into equal blocks to get scale-invariant features.Weber law has been used for getting texture features,and finally,XGBOOST is used to classify both Copy-Move and splicing forgery.The proposed method classified three types of forgeries,i.e.,splicing,Copy-Move,and healthy.Benchmarked(CASIA 2.0,MICCF200)and RCMFD datasets are used for training and testing.On average,the proposed method achieved 97.3% accuracy on benchmarked datasets and 98.3% on RCMFD datasets by applying 10-fold cross-validation,which is far better than existing methods.

Similarity measure design on overlapped and non-overlapped data

Similarity measure design on non-overlapped data was carried out and compared with the case of overlapped data.Unconsistant feature of similarity on overlapped data to non-overlapped data was provided by example.By the artificial data illustration,it was proved that the conventional similarity measure was not proper to calculate the similarity measure of the non-overlapped case.To overcome the unbalance problem,similarity measure on non-overlapped data was obtained by considering neighbor information.Hence,different approaches to design similarity measure were proposed and proved by consideration of neighbor information.With the example of artificial data,similarity measure calculation was carried out.Similarity measure extension to intuitionistic fuzzy sets(IFSs)containing uncertainty named hesitance was also followed.

A Spacecra Equipment Layout Optimization Method for Diverse and Competitive Design

The spacecraequipment layout optimization design(SELOD)problems with complicated performance con-straints and diversity are studied in this paper.The previous literature uses the gradient-based algorithm to obtain optimized non-overlap layout schemes from randomly initialized cases eectively.However,these local optimal solutions are too dicult to jump out of their current relative geometry relationships,signi􀀀cantly limiting their further improvement in performance indicators.Therefore,considering the geometric diversity of layout schemes is put forward to alleviate this limitation.First,similarity measures,including modi􀀀ed cosine similarity and gaussian kernel function similarity,are introduced into the layout optimization process.Then the optimization produces a set of feasible layout candidates with the most remarkable dierence in geometric distribution and the most representative schemes are sampled.Finally,these feasible geometric solutions are used as initial solutions to optimize the physical performance indicators of the spacecra,and diversi􀀀ed layout schemes of spacecraequipment are generated for the engineering practice.The validity and eectiveness of the proposed methodology are demonstrated by two SELOD applications.

Global Calibration Method of Multi-sensor Vision System Using Skew Laser Lines

Multi-sensor vision system plays an important role in the 3D measurement of large objects.However,due to the widely distribution of sensors,the problem of lacking common fields of view（FOV） arises frequently,which makes the global calibration of the vision system quite difficult.The primary existing solution relies on large-scale surveying equipments,which is ponderous and inconvenient for field calibrations.In this paper,a global calibration method of multi-sensor vision system is proposed and investigated.The proposed method utilizes pairs of skew laser lines,which are generated by a group of laser pointers,as the calibration objects.Each pair of skew laser lines provides a unique coordinate system in space which can be reconstructed in certain vision sensor＇s coordinates by using a planar pattern.Then the geometries of sensors are computed under rigid transformation constrains by taking coordinates of each skew lines pair as the intermediary.The method is applied on both visual cameras with synthetic data and a real two-camera vision system;results show the validity and good performance.The prime contribution of this paper is taking skew laser lines as the global calibration objects,which makes the method simple and flexible.The method need no expensive equipments and can be used in large-scale calibration.

Domain Decomposition of an Optimal Control Problem for Semi-Linear Elliptic Equations on Metric Graphs with Application to Gas Networks

We consider optimal control problems for the flow of gas in a pipe network. The equations of motions are taken to be represented by a semi-linear model derived from the fully nonlinear isothermal Euler gas equations. We formulate an optimal control problem on a given network and introduce a time discretization thereof. We then study the well-posedness of the corresponding time-discrete optimal control problem. In order to further reduce the complexity, we consider an instantaneous control strategy. The main part of the paper is concerned with a non-overlapping domain decomposition of the semi-linear elliptic optimal control problem on the graph into local problems on a small part of the network, ultimately on a single edge.

Efficiency of Two-Stage Adaptive Cluster Sampling Design in Estimating Fringe-Eared Oryx

Two-stage adaptive cluster sampling and two-stage conventional sampling designs were used to estimate population total of Fringe-Eared Oryx that are clustered and sparsely distributed. The study region was Amboseli-West Kilimanjaro and Magadi-Natron cross boarder landscape between Kenya and Tanzania. The study region was partitioned into different primary sampling units with different secondary sampling units that were of different sizes. Results show that two-stage adaptive cluster sampling design is efficient compared to simple random sampling and the conventional two- stage sampling design. The design is less variable compared to the conventional two-stage sampling design.

In situ method for stress measurements in film-substrate electrodes during electrochemical processes:key role of softening and stiffening

Electrode stress is one of the main driving forces of electrochemical degradation,which is directly related to battery cycle life,thus attracting great interest.Herein,we propose an in situ method to measure bilayer stresses in film-substrate electrodes during electrochemical processes.This method consists of two parts:stress models featuring Li-dependent material modulus and in situ deformation measurements,through which electrode bilayer stresses evolution accompanied by Li-dependent material modulus can be quantitatively characterized.As application of the method,typical silicon-composite and carbon-composite film-substrate electrodes are selected for in situ mechanical measurements and experimental analysis is performed.Results show that silicon material and carbon material exhibit significant,continuous softening and stiffening,respectively.In two film-substrate electrodes,electrode material films experience compressive stress and current collector substrates undergo a tensile-to-compressive conversion across the thickness.Besides,moduli and stresses in both electrodes vary nonlinearly with capacity,presenting non-overlapping paths between lithiation and delithiation.Based on experimental data,we further demonstrate the key role of Li-dependent modulus on electrode stresses,finding that silicon material softening decreases and carbon material stiffening increases electrode stresses.The deficiencies of current stress measurement method based on Stoney equation and the applicability of our method are discussed.

A clock generator for a high-speed high-resolution pipelined A/D converter

A clock generator circuit for a high-speed high-resolution pipelined A/D converter is presented. The circuit is realized by a delay locked loop （DLL）, and a new differential structure is used to improve the precision of the charge pump. Meanwhile, a dynamic logic phase detector and a three transistor NAND logic circuit are proposed to reduce the output jitter by improving the steepness of the clock transition. The proposed circuit, designed by SMIC 0.18 um 3.3 V CMOS technology, is used as a clock generator for a 14 bit 100 MS/s pipelined ADC. The simulation results have shown that the duty cycle ranged from 10% to 90% and can be adjusted. The average duty cycle error is less than 1%. The lock-time is only 13 clock cycles. The active area is 0.05 mm2 and power consumption is less than 15 mW.