Results 221 to 230 of about 3,861,419 (280)
Robust Cubature Kalman Filter for Moving-Target Tracking with Missing Measurements. [PDF]
Sensors (Basel)Sahl S, Song E, Niu D.
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IFAC Proceedings Volumes, 1990
Abstract This paper presents studies of techniques for tracking multiple targets using a track splitting, or branching approach. The filters used for tracking targets moving in the x-y plane were α-β filters. Two a-s filters for each tracked target were used; one for each coordinate axis.
C.A. Deacon, D.P. Atherton
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Abstract This paper presents studies of techniques for tracking multiple targets using a track splitting, or branching approach. The filters used for tracking targets moving in the x-y plane were α-β filters. Two a-s filters for each tracked target were used; one for each coordinate axis.
C.A. Deacon, D.P. Atherton
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Target recognition and tracking
International Journal of Systems Science, 2001Advances in image and signal processing permit implementation of sophisticated sensor fusion algorithms for tracking and target identification. The polymoprhic estimator (PME) accomplishes these tasks simultaneously. However, it has been observed that there is an identification bias toward more languorous targets.
David D. Sworder, John E. Boyd
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IEEE International Conference on Image Processing 2005, 2005
In this paper, the problem of continuous tracking of moving objects with a PTZ camera is addressed. In particular, the problem of tracking moving objects during zoom phases is solved by using a feature clustering technique. In order to adopt such a method, we need, first, a step where during tracking with a pan&tilt camera we can identify the mobile ...
MICHELONI, Christian, FORESTI, Gian Luca
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In this paper, the problem of continuous tracking of moving objects with a PTZ camera is addressed. In particular, the problem of tracking moving objects during zoom phases is solved by using a feature clustering technique. In order to adopt such a method, we need, first, a step where during tracking with a pan&tilt camera we can identify the mobile ...
MICHELONI, Christian, FORESTI, Gian Luca
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Learning to Track Multiple Targets
IEEE Transactions on Neural Networks and Learning Systems, 2015Monocular multiple-object tracking is a fundamental yet under-addressed computer vision problem. In this paper, we propose a novel learning framework for tracking multiple objects by detection. First, instead of heuristically defining a tracking algorithm, we learn that a discriminative structure prediction model from labeled video data captures the ...
Xiao Liu 0012 +5 more
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The intent inference in target tracking based on the target track
2014 IEEE International Conference on System Science and Engineering (ICSSE), 2014The detection of anomalous trajectory patterns in target tracking is considered here to infer the target's intent which is assumed to be related to the shape of the target's trajectory. The context-free grammar is used to model the trajectory of the target and obtain the mode sequence via the quantification to the state estimate.
null Huan He, null Chongzhao Han
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A tracking algorithm of maneuvering targets
[1992] Proceedings of the 31st IEEE Conference on Decision and Control, 1993A methodology for the tracking of maneuvering targets is presented. The authors' algorithm uses a quickest detection scheme based on the innovation sequence that minimizes the maneuver detection delay. Their approach also includes a recursive technique to maneuver magnitude estimation and a modified Kalman filter that incorporates the maneuver ...
T.C. Wang, P.K. Varshney
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On tracking multiple indistinguishable targets
2012 IEEE 9th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS 2012), 2012In this paper, we propose a generic approach to tracking multiple indistinguishable moving targets with wireless sensor networks. The tracking algorithm first separates the aggregate signals from multiple indistinguishable targets via the Blind Source Separation (BSS) method.
Ye Zhu 0001, Anil Vikram, Huirong Fu
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Wideband multiple target tracking
Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing, 2002We propose a new scheme involving autoregressive parameter estimation and pattern classification with maximum likelihood (ML) direction of arrival (DOA) estimation to track multiple targets moving in the far-field. The targets are sources of wideband signals which impinge on a uniform linear array of passive sensors.
A. Satish, Rangasami L. Kashyap
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