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tracking Maneuvering Group Target with Extension Predicted and Best Model Augmentation Method Adapted

MATHEMATICAL PROBLEMS IN ENGINEERING 2017年第1期2017卷 1-9页

作者： Gan, Linhai Wang, Gang Air Force Engn Univ Air & Missile Def Coll Xian Shaanxi Peoples R China

The random matrix (RM) method is widely applied for group target tracking. The assumption that the group extension keeps invariant in conventional RM method is not yet valid, as the orientation of the group varies rapidly while it is maneuvering;thus, a new approach with group extension predicted is derived here. To match the group maneuvering, a best model augmentation (BMA) method is introduced. The existing BMA method uses a fixed basic model set, which may lead to a poor performance when it could not ensure basic coverage of true motion modes. Here, a maneuvering group target tracking algorithm is proposed, where the group extension prediction and the BMA adaption are exploited. The performance of the proposed algorithm will be illustrated by simulation.

关键词： MANEUVERING boards RANDOM matrices tracking algorithms SIMULATION methods & models PREDICTION models

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Online multi-person tracking with two-stage data association and online appearance model learning

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IET COMPUTER VISION 2017年第1期11卷 87-95页

作者： Ju, Jaeyong Kim, Daehun Ku, Bonhwa Han, David K. Ko, Hanseok Korea Univ Sch Elect Engn Seoul South Korea Off Naval Res Arlington VA USA

This study addresses the automatic multi-person tracking problem in complex scenes from a single, static, uncalibrated camera. In contrast with offline tracking approaches, a novel online multi-person tracking method is proposed based on a sequential tracking-by-detection framework, which can be applied to real-time applications. A two-stage data association is first developed to handle the drifting targets stemming from occlusions and people's abrupt motion changes. Subsequently, a novel online appearance learning is developed by using the incremental/ decremental support vector machine with an adaptive training sample collection strategy to ensure reliable data association and rapid learning. Experimental results show the effectiveness and robustness of the proposed method while demonstrating its compatibility with real-time applications.

关键词： tracking algorithms CAMERAS REAL-time computing SUPPORT vector machines COMPUTER vision

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Online visual tracking based on subspace representation with continuous occlusion modeling

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MULTIMEDIA SYSTEMS 2017年第3期23卷 357-368页

作者： Bo, Chunjuan Zhang, Junxing Liu, Changhong Yao, Qiang Dalian Nationalities Univ Coll Electromech Engn Dalian 116600 Peoples R China Dalian Nationalities Univ Coll Informat & Commun Engn Dalian 116600 Peoples R China

As an important issue in image processing and computer vision, online visual tracking acts a critical role in numerous lines of research and has many potential applications. This paper presents a novel tracking algorithm based on subspace representation with continuous occlusion handling, the contributions of which are threefolds. First, this paper develops an effective objective function to represent the tracked object, in which the object reconstruction, the sparsity of the error term and the spatial consistency of the error term are simultaneously considered. Then, we derive an iterative algorithm to solve the proposed objective function based on the accelerated proximal gradient framework, and therefore obtain the optimal representation coefficients and the possible occlusion conditions. Finally, based on the proposed representation model, we design an effective likelihood function and a simple model update scheme for building a robust tracker within the particle filter framework. We conduct many experiments to evaluate the proposed tracking algorithm in comparisons with other state-of-the-art trackers. Both qualitative and quantitative evaluations demonstrate the proposed tracker achieves good performance.

关键词： SUBSPACE identification (Mathematics) COMPUTER vision MULTIPLE correspondence analysis (Statistics) tracking algorithms IMAGE processing -- Mathematical models

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Distributed tracking of heterogeneous nonlinear fractional-order multi-agent systems with an unknown leader

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JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2017年第5期354卷 2226-2244页

作者： Gong, Ping Xiamen Univ Dept Automat Xiamen 361005 Fujian Peoples R China

By applying the fractional Lyapunov direct method, this paper investigates the distributed tracking problem of nonlinear fractional-order multi-agent systems subject to heterogeneous control gains and a time-varying leader whose input is unknown and bounded over a general directed graph. Due to the existence of heterogeneous control gains as well as a time-varying unknown leader in the nonlinear systems, the fractional-order dynamics of each agent is in essence heterogeneous. At first, a discontinuous distributed controller is constructed to guarantee that the distributed tracking control problem can be solved if some conditions are satisfied. Next, a continuous distributed controller is further proposed to eliminate the undesirable chattering phenomenon of the discontinuous controller, where the upper bound of the tracking error is uniformly bounded and can be made small enough by choosing the parameters appropriately. Finally, some simulation examples are presented to verify the effectiveness of the main results. (C) 2017 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

关键词： NONLINEAR functions MULTIAGENT systems tracking algorithms PROBLEM solving TIME-varying systems

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Visual tracking Based on Complementary Learners with Distractor Handling

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MATHEMATICAL PROBLEMS IN ENGINEERING 2017年第1期2017卷 1-13页

作者： Wibowo, Suryo Adhi Lee, Hansoo Kim, Eun Kyeong Kim, Sungshin Pusan Natl Univ Dept Elect & Comp Engn Busan South Korea

The representation of the object is an important factor in building a robust visual object tracking algorithm. To resolve this problem, complementary learners that use color histogram-and correlation filter-based representation to represent the target object can be used since they each have advantages that can be exploited to compensate the other's drawback in visual tracking. Further, a tracking algorithm can fail because of the distractor, even when complementary learners have been implemented for the target object representation. In this study, we show that, in order to handle the distractor, first the distractor must be detected by learning the responses fromthe color-histogram-and correlation-filter-based representation. Then, to determine the target location, we can decide whether the responses from each representation should be merged or only the response from the correlation filter should be used. This decision depends on the result obtained from the distractor detection process. Experiments were performed on the widely used VOT2014 and VOT2015 benchmark datasets. It was verified that our proposed method performs favorably as compared with several state-of-the-art visual tracking algorithms.

关键词： OBJECT tracking (Computer vision) HISTOGRAMS tracking algorithms CORRELATION (Statistics) DATA analysis

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Markov chain Monte Carlo based video tracking algorithm

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PROGRAMMING AND COMPUTER SOFTWARE 2017年第4期43卷 224-229页

作者： Kuplyakov, D. Shalnov, E. Konushin, A. Moscow MV Lomonosov State Univ Dept Computat Math & Cybernet Moscow 119991 Russia NRU Higher Sch Econ Moscow 101000 Russia

The paper considers a problem of multiple person tracking. We present the algorithm to automatic people tracking on surveillance videos recorded by static cameras. Proposed algorithm is an extension of approach based on tracking-by-detection of people heads and data association using Markov chain Monte Carlo (MCMC). Short track fragments (tracklets) are built by local tracking of people heads. Tracklet postprocessing and accurate results interpolation were shown to reduce number of false positives. We use position deviations of tracklets and revised entry/exit points factor to separate pedestrians from false positives. The paper presents a new method to estimate body position, that increases precision of tracker. Finally, we switched HOG-based detector to cascade one. Our evaluation shows proposed modifications significantly increase tracking quality.

关键词： MARKOV chain Monte Carlo DIGITAL video tracking algorithms VIDEO surveillance DIGITAL cameras

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Optical signal processing and tracking of whispering gallery modes in real-time for sensing applications 4

Optical signal processing and tracking of whispering gallery...

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Conference on Integrated Photonics - Materials, Devices, and Applications IV

作者： Ali, Amir R. Afifi, Amr N. Taha, Hazem German Univ Cairo Dept Mech Engn Appl Sci & Robot Lab Applied Mechatron ARatron La New Cairo 11835 Egypt Southern Methodist Univ Dept Mech Engn Microsensor Lab Dallas TX 75275 USA

ISBN: (数字)9781510610002

ISBN: (纸本)9781510609990;9781510610002

A novel approach for tracking of whispering gallery modes (WGM) in real-time for dielectric cavities used in sensing application is presented in this paper. Real-time tracking for the shifts of the WGM can be used to measure the physical quantity of interest precisely, under high repetition rates. The tracking algorithm is based on cross-correlation signal processing technique which has been proved to be accurate in WGM shifts detection. In order to achieve portability, the aforementioned real-time algorithm is implemented using a single-board re-configurable input-output hardware. The hardware platform used combines a real-time processor and a field programmable gate array (FPGA), it also allows for data exchange between them. The tracking algorithm's accuracy and real-time behavior is verified by preforming simulations based on experiments conducted on the dielectric cavity, where the cavity is used as a force sensor measuring mechanical compression. The light from a laser diode is tuned with rates up to 10 kHz and then tangentially coupled into the cavity to excite the WGM. Results show that shifts of the WGM are tracked by the algorithm providing real-time force readings.

关键词： Signal processing whispering gallery mode micro-cavities optical MEMS real-time tracking algorithms FPGA sensing applications

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Dissipative boundary conditions for 2 x 2 hyperbolic systems of conservation laws for entropy solutions in BY

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JOURNAL OF DIFFERENTIAL EQUATIONS 2017年第1期262卷 1-30页

作者： Coron, Jean-Michel Ervedoza, Sylvain Ghoshal, Shyam Sundar Glass, Olivier Perrollaz, Vincent Univ Paris 06 Sorbonne Univ CNRS UMR 7598 Lab Jacques Louis Lions 4 Pl Jussieu F-75252 Paris 05 France Univ Toulouse 3 Inst Math Toulouse CNRS UMR 5219 118 Route Narbonne F-31062 Toulouse 9 France GSSI Viale Francesco Crispi 7 I-67100 Laquila Italy Univ Paris 09 CEREMADE CNRS UMR 7534 Pl Marechal Lame Tassigny F-75775 Paris 16 France Univ Tours CNRS UMR 7350 Lab Math & Phys Theor Parc Grandmont F-37200 Tours France

In this article, we investigate the BV stability of 2 x 2 hyperbolic systems of conservation laws with strictly positive velocities under dissipative boundary conditions. More precisely, we derive sufficient conditions guaranteeing the exponential stability of the system under consideration for entropy solutions in By. Our proof is based on a front tracking algorithm used to construct approximate piecewise constants solutions whose BV norms are controlled through a Lyapunov functional. This Lyapunov functional is inspired by the one proposed in J. Glimm's seminal work [16], modified with some suitable weights in the spirit of the previous works [10,9].

关键词： BOUNDARY value problems HYPERBOLIC functions CONSERVATION laws (Mathematics) EXPONENTIAL stability LYAPUNOV functions tracking algorithms

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Rate-induced tipping from periodic attractors: Partial tipping and connecting orbits

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CHAOS 2018年第3期28卷 033608-033608页

作者： Alkhayuon, Hassan M. Ashwin, Peter Univ Exeter Ctr Syst Dynam & Control Dept Math Exeter EX4 4QF Devon England

We consider how breakdown of the quasistatic approximation for attractors can lead to rate-induced tipping, where a qualitative change in tracking/tipping behaviour of trajectories can be characterised in terms of a critical rate. Associated with rate-induced tipping (where tracking of a branch of quasistatic attractors breaks down), we find a new phenomenon for attractors that are not simply equilibria: partial tipping of the pullback attractor where certain phases of the periodic attractor tip and others track the quasistatic attractor. For a specific model system with a parameter shift between two asymptotically autonomous systems with periodic attractors, we characterise thresholds of rate-induced tipping to partial and total tipping. We show these thresholds can be found in terms of certain periodic-to-periodic and periodic-to-equilibrium connections that we determine using Lin's method for an augmented system. Published by AIP Publishing.

关键词： tracking algorithms ATTRACTORS (Mathematics) QUASISTATIC processes AUGMENTED reality BIFURCATION theory

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Visual Vehicle tracking Based on Deep Representation and Semisupervised Learning

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JOURNAL OF SENSORS 2017年第3-9期2017卷 6471250-6471250页

作者： Cai, Yingfeng Wang, Hai Sun, Xiao-qiang Chen, Long Jiangsu Univ Automot Engn Res Inst Zhenjiang 212013 Jiangsu Peoples R China Jiangsu Univ Sch Automot & Traff Engn Zhenjiang 212013 Jiangsu Peoples R China

Discriminative tracking methods use binary classification to discriminate between the foreground and background and have achieved some useful results. However, the use of labeled training samples is insufficient for them to achieve accurate tracking. Hence, discriminative classifiers must use their own classification results to update themselves, which may lead to feedback-induced tracking drift. To overcome these problems, we propose a semisupervised tracking algorithm that uses deep representation and transfer learning. Firstly, a 2D multilayer deep belief network is trained with a large amount of unlabeled samples. The nonlinear mapping point at the top of this network is subtracted as the feature dictionary. Then, this feature dictionary is utilized to transfer train and update a deep tracker. The positive samples for training are the tracked vehicles, and the negative samples are the background images. Finally, a particle filter is used to estimate vehicle position. We demonstrate experimentally that our proposed vehicle tracking algorithm can effectively restrain drift while also maintaining the adaption of vehicle appearance. Compared with similar algorithms, our method achieves a better tracking success rate and fewer average central-pixel errors.

关键词： tracking algorithms Supervised learning (Machine learning) Error analysis (Mathematics) Feedback control systems Image analysis

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