Monroeville, PA, United States
Monroeville, PA, United States

Time filter

Source Type

Chenouard N.,Institute Pasteur Paris | Chenouard N.,Ecole Polytechnique Federale de Lausanne | Chenouard N.,New York University | Smal I.,Erasmus Medical Center | And 37 more authors.
Nature Methods | Year: 2014

Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers. © 2014 Nature America, Inc.


Coraluppi S.,Compunetix Inc. | Carthel C.,Compunetix Inc.
Proceedings of the 16th International Conference on Information Fusion, FUSION 2013 | Year: 2013

This paper introduces a generalization of the multiple-hypothesis tracking (MHT) formalism for multi-target tracking (MTT). To our knowledge, MHT treatments in the literature do not consider undetected target birth events. Their inclusion leads to an interesting extension to the MHT recursion, and necessitates aggregation over indistinguishable global hypotheses. We show that the MHT recursion factors, enabling track-oriented MHT (TO-MHT), albeit with clusters of indistinguishable undetected births. The treatment requires a distinction between those targets that are eventually detected (we call these unnoticed targets) and those that are never detected (we call these ghost targets). The same number of relevant track hypotheses result as in the classical TO-MHT solution. In the time-invariant case, the solution simplifies further. © 2013 ISIF ( Intl Society of Information Fusi.


Coraluppi S.,Compunetix Inc. | Carthel C.,Compunetix Inc.
15th International Conference on Information Fusion, FUSION 2012 | Year: 2012

This paper describes a fusion architecture that enables multi-level object tracking. The motivation is provided by the fusion of active and passive data, where multiple passive contacts may originate from the same platform at a given time. This poses a significant challenge to those target-tracking algorithms that are based on the assumption that each sensor provides at most one contact per target per scan or processing interval. For example, while each object has a unique radar return (except when considering extended objects with multiple reflectors), multiple passive contacts may arise when multiple emitter modes are onboard. Simulation results demonstrate the potential of the proposed architecture. © 2012 ISIF (Intl Society of Information Fusi).


Coraluppi S.,Compunetix Inc.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2012

Fusion of passive electronic support measures (ESM) with active radar data enables tracking and identification of platforms in air, ground, and maritime domains. An effective multi-sensor fusion architecture adopts hierarchical real-time multi-stage processing. This paper focuses on the recursive filtering challenges. The first challenge is to achieve effective platform identification based on noisy emitter type measurements; we show that while optimal processing is computationally infeasible, a good suboptimal solution is available via a sequential measurement processing approach. The second challenge is to process waveform feature measurements that enable disambiguation in multi-target scenarios where targets may be using the same emitters. We show that an approach that explicitly considers the Markov jump process outperforms the traditional Kalman filtering solution. © 2012 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).


Coraluppi S.,Compunetix Inc. | Carthel C.,Compunetix Inc.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2012

Multi-target filtering for closely-spaced targets leads to degraded performance with respect to single-target filtering solutions, due to measurement provenance uncertainty. Soft data association approaches like the probabilistic data association filter (PDAF) suffer track coalescence. Conversely, hard data association approaches like multiple-hypothesis tracking (MHT) suffer track repulsion. We introduce the stochastic data association filter (SDAF) that utilizes the PDAF weights in a stochastic, hard data association update step. We find that the SDAF outperforms the PDAF, though it does not match the performance of the MHT solution. We compare as well to the recently-introduced equivalence-class MHT (ECMHT) that successfully counters the track repulsion effect. Simulation results are based on the steady-state form of the Ornstein-Uhlenbeck process, allowing for lengthy stochastic realizations with closely-spaced targets. © 2012 SPIE.


Coraluppi S.,Compunetix Inc. | Carthel C.,Compunetix Inc.
IEEE Aerospace Conference Proceedings | Year: 2014

This paper studies the counting-targets limit of the multiple-hypothesis tracking (MHT) and cardinalized probability hypothesis density (CPHD) solutions to the multi-target tracking (MTT) problem. The solutions are compared with a direct Kalman filtering (KF) solution to the counting-targets MTT problem, whereby we assume a continuous state (number of objects) and assume linear Gaussian measurements. While the enhanced MHT solution - the cardinalized MHT (CMHT) - performs well, it does not match the performance of the KF and of the CPHD. In future work, we will assess these solutions with an RMSE performance metric and examine whether there is any sub-optimality in the CPHD solution to this problem. © 2014 IEEE.


Coraluppi S.,Compunetix Inc. | Carthel C.A.,Compunetix Inc.
IEEE Transactions on Aerospace and Electronic Systems | Year: 2014

This paper introduces a generalization of the multiple-hypothesis tracking (MHT) formalism for multitarget tracking. To our knowledge, MHT treatments in the literature do not consider undetected target birth events. Their inclusion leads to an interesting extension to the MHT recursion and necessitates aggregation over indistinguishable global hypotheses. We show that the MHT recursion factors, enabling track-oriented MHT (TO-MHT), albeit with clusters of indistinguishable undetected births. The treatment requires a distinction between those targets that are eventually detected (we call these unnoticed targets) and those that are never detected (we call these ghost targets). While the formulation appears more complex, there is structure to the solution that can be exploited, resulting in the same number of relevant track hypotheses for detected targets as in the classical TO-MHT solution. In the time-invariant case, the solution simplifies further because we need not consider unnoticed targets and there is a fixed structure to the ghost target solution. © 2014 IEEE.


Katsilieris F.,Center for Maritime | Braca P.,Center for Maritime | Coraluppi S.,Compunetix Inc.
Proceedings of the 16th International Conference on Information Fusion, FUSION 2013 | Year: 2013

The Automatic Identification System (AIS) is an automatic tracking system based on reports provided by the vessels carrying an AIS transponder. The reports contain information on the vessel position, velocity etc. and typically have high accuracy. Given that the AIS is a self-reporting system, the trustworthiness of positional information depends on data being reported by the vessel, rather than measured by a sensor. Any self-reporting system is prone to 'spoofing' or the intentional reporting on incorrect information. This paper addresses the inference problem of whether the received AIS data are trustworthy with the help of radar measurements and information from the tracking system. This problem can be treated in the hypothesis testing framework where the null hypothesis is that the AIS data are trustworthy and the alternative hypothesis is that the data are spoofed. The proposed solution, the generalized version of the sequential log-likelihood ratio test, is compared to the ideally optimal solution using real and simulated data. © 2013 ISIF ( Intl Society of Information Fusi.


Trademark
Compunetix Inc. | Date: 2016-06-18

Telecommunications Media Processor for real-time communications (RTC) applications, including conferencing of 3 or more locations simultaneously (i.e. conferencing bridges); or other RTC applications such as those to support multipoint for WebRTC, IMS, High Definition (HD), and secure communications solutions.


Trademark
Compunetix Inc. | Date: 2011-03-01

telecommunications conferencing equipment for conference calls from three or more remote locations, namely, conferencing bridges.

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