Yearly Archives: 2016

HW-SW Codesign of a Positioning System: From UML to Implementation Case Study

HW-SW Codesign of a Positioning System: From UML to Implementation Case Study

  • Angel Alvarez, Inigo Ugarte, Patricia Martinez, and Victor Fernandez. HW-SW Codesign of a Positioning System: From UML to Implementation Case Study. In Proceedings of the 2016 Conference on Design of Circuits and Integrated Systems (DCIS), pages 1-6, Grenada, Spain, 2016. doi:10.1109/DCIS.2016.7845378
    [BibTeX]
    @InProceedings{2016-11-ALVAREZ,
    author = {Angel Alvarez and Inigo Ugarte and Patricia Martinez and Victor Fernandez},
    title = {{HW-SW Codesign of a Positioning System: From UML to Implementation Case Study}},
    booktitle = {{Proceedings of the 2016 Conference on Design of Circuits and Integrated Systems (DCIS)}},
    date = {2016-11-23/2016-11-25},
    year = {2016},
    doi = {10.1109/DCIS.2016.7845378},
    address = {Grenada, Spain},
    pages = {1-6}
    }

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Smart Vision Meets Communication

Smart Vision Meets Communication

  • Andrea Cavallaro. Smart Vision Meets Communication. Invited talk at Advanced Concepts for Intelligent Vision Systems 2016, 2016.
    [BibTeX]
    @Misc{2016-10-CAVALLAROa,
    author = {Andrea Cavallaro},
    title = {{Smart Vision Meets Communication}},
    howpublished = {Invited talk at Advanced Concepts for Intelligent Vision Systems 2016},
    date = {2016-10-24/2016-10-27},
    year = {2016},
    address = {Lecce, Italy}
    }

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Application-layer rate-adaptive multicast video streaming over 802.11 for mobile devices

Application-layer rate-adaptive multicast video streaming over 802.11 for mobile devices

  • Raheeb Muzaffar, Evsen Yanmaz, Christian Bettstetter, and Andrea Cavallaro. Application-layer rate-adaptive multicast video streaming over 802.11 for mobile devices. In Proceedings of the 24th ACM international conference on Multimedia, pages 506-510, Amsterdam, The Netherlands, 2016. doi:10.1145/2964284.2967272
    [BibTeX] [Abstract]

    Multicast video streaming over IEEE 802.11 is unreliable due to the lack of feedback from receivers. High data rates and variable link conditions require feedback from the receivers for link estimation to improve reliability and rate adaptation accordingly. In this paper, we validate on a test platform an application-layer rate-adaptive video multicast streaming framework using an 802.11 ad-hoc network applicable for mobile senders and receivers. Experimental results serve as a proof of concept and show the performance in terms of goodput, delay, packet loss, and received video quality.

    @InProceedings{2016-10-MUZAFFAR,
    title = {{Application-layer rate-adaptive multicast video streaming over 802.11 for mobile devices}},
    author = {Raheeb Muzaffar and Evsen Yanmaz and Christian Bettstetter and Andrea Cavallaro},
    booktitle = {{Proceedings of the 24th ACM international conference on Multimedia}},
    address= {Amsterdam, The Netherlands},
    date = {2016-10-15/2016-10-19},
    year = {2016},
    pages = {506-510},
    doi = {10.1145/2964284.2967272},
    abstract = {Multicast video streaming over IEEE 802.11 is unreliable due to the lack of feedback from receivers. High data rates and variable link conditions require feedback from the receivers for link estimation to improve reliability and rate adaptation accordingly. In this paper, we validate on a test platform an application-layer rate-adaptive video multicast streaming framework using an 802.11 ad-hoc network applicable for mobile senders and receivers. Experimental results serve as a proof of concept and show the performance in terms of goodput, delay, packet loss, and received video quality.}
    }

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Smart Cameras and Privacy

Smart Cameras and Privacy

  • Andrea Cavallaro. Smart Cameras and Privacy. Invited talk at IC1206 Training School: De-identification for Privacy Protection in Multimedia Content, 2016.
    [BibTeX]
    @Misc{2016-10-CAVALLAROb,
    author = {Andrea Cavallaro},
    title = {{Smart Cameras and Privacy}},
    howpublished = {Invited talk at IC1206 Training School: De-identification for Privacy Protection in Multimedia Content},
    date = {2016-10-07/2016-10-11},
    year = {2016},
    address = {Limassol, Cyprus}
    }

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Online multi-target tracking with strong and weak detections

Online multi-target tracking with strong and weak detections

  • Ricardo Sanchez-Matilla, Fabio Poiesi, and Andrea Cavallaro. Online multi-target tracking with strong and weak detections. In Proceedings of European Conference on Computer Vision Workshop: 2nd Workshop on Benchmarking Multi-target Tracking: MOTChallenge 2016, pages 1-16, Amsterdam, The Netherlands, 2016.
    [BibTeX] [Abstract] [Download PDF]

    We propose an online multi-target tracker that exploits both high- and low-confidence target detections in a Probability Hypothesis Density Particle Filter framework. High-confidence (strong) detections are used for label propagation and target initialization. Low-confidence (weak) detections only support the propagation of labels, i.e. tracking existing targets. Moreover, we perform data association just after the prediction stage thus avoiding the need for computationally expensive labeling procedures such as clustering. Finally, we perform sampling by considering the perspective distortion in the target observations. The tracker runs on average at 12 frames per second. Results show that our method outperforms alternative online trackers on the Multiple Object Tracking 2016 and 2015 benchmark datasets in terms tracking accuracy, false negatives and speed.

    @InProceedings{2016-10-MATILLA,
    title = {{Online multi-target tracking with strong and weak detections}},
    author = {Ricardo Sanchez-Matilla and Fabio Poiesi and Andrea Cavallaro},
    booktitle = {{Proceedings of European Conference on Computer Vision Workshop: 2nd Workshop on Benchmarking Multi-target Tracking: MOTChallenge 2016}},
    address= {Amsterdam, The Netherlands},
    date = {2016-10-09},
    year = {2016},
    pages = {1-16},
    url = {http://www.eecs.qmul.ac.uk/~andrea/papers/2016_ECCVW_MOT_OnlineMTTwithStrongAndWeakDetections_Sanchez-Matilla_Poiesi_Cavallaro.pdf},
    abstract = {We propose an online multi-target tracker that exploits both high- and low-confidence target detections in a Probability Hypothesis Density Particle Filter framework. High-confidence (strong) detections are used for label propagation and target initialization. Low-confidence (weak) detections only support the propagation of labels, i.e. tracking existing targets. Moreover, we perform data association just after the prediction stage thus avoiding the need for computationally expensive labeling procedures such as clustering. Finally, we perform sampling by considering the perspective distortion in the target observations. The tracker runs on average at 12 frames per second. Results show that our method outperforms alternative online trackers on the Multiple Object Tracking 2016 and 2015 benchmark datasets in terms tracking accuracy, false negatives and speed.}
    }

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Transforming VHDL Descriptions into Formal Component-based Models

Transforming VHDL Descriptions into Formal Component-based Models

  • Ayoub Nouri, Rahma Ben Atitallah, Anca Molnos, Christian Fabre, Frédéric Heitzmann, and Olivier Debicki. Transforming VHDL Descriptions into Formal Component-based Models. In Proceedings of 27th IEEE International Symposium on Rapid System Prototyping (RSP), Pittsburgh, PA, USA, 2016. To appear doi:10.1145/2990299.2990320
    [BibTeX]
    @InProceedings{2016-10-NOURI,
    author = {Ayoub Nouri and Rahma Ben Atitallah and Anca Molnos and Christian Fabre and Fr\'{e}d\'{e}ric Heitzmann and Olivier Debicki},
    title = {{Transforming VHDL Descriptions into Formal Component-based Models}},
    booktitle = {{Proceedings of 27th IEEE International Symposium on Rapid System Prototyping (RSP)}},
    date = {2016-10-06/2016-10-07},
    year = {2016},
    doi = {10.1145/2990299.2990320},
    note = {To appear},
    address = {Pittsburgh, PA, USA}
    }

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From a Formalized Parallel Action Language to its Efficient Code Generation

From a Formalized Parallel Action Language to its Efficient Code Generation

  • Ivan Llopard, Christian Fabre, and Albert Cohen. From a Formalized Parallel Action Language to its Efficient Code Generation. ACM Transactions on Embedded Computing Systems, 16(2), 2016. doi:10.1145/2990195
    [BibTeX] [Abstract]

    Modeling languages propose convenient abstractions and transformations to handle the complexity of s embedded systems. Based on the formalism of Hierarchical State Machine, they enable the expression of hierarchical control parallelism. However, they face two importants challenges when it comes to model data-intensive applications: no unified approach that also accounts for data-parallel actions; and no effective code optimization and generation flows. We propose a modeling language extended with parallel action semantics and hierarchical indexed-state machines suitable for computationally intensive applications. Together with its formal semantics, we present an optimizing model compiler aiming for the generation of efficient data-parallel implementations.

    @Article{2016-09-LLOPARD,
    author = {Ivan Llopard and Christian Fabre and Albert Cohen},
    journal = {{ACM Transactions on Embedded Computing Systems}},
    title = {{From a Formalized Parallel Action Language to its Efficient Code Generation}},
    year = {2016},
    date = {2016-09},
    volume = {16},
    number = {2},
    doi = {10.1145/2990195},
    abstract = {Modeling languages propose convenient abstractions and transformations to handle the complexity of s embedded systems. Based on the formalism of Hierarchical State Machine, they enable the expression of hierarchical control parallelism. However, they face two importants challenges when it comes to model data-intensive applications: no unified approach that also accounts for data-parallel actions; and no effective code optimization and generation flows. We propose a modeling language extended with parallel action semantics and hierarchical indexed-state machines suitable for computationally intensive applications. Together with its formal semantics, we present an optimizing model compiler aiming for the generation of efficient data-parallel implementations.}
    }

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Application of Drones and Acoustic and Visual Sensors in Remote Detection and Localization of Objects and Events

Application of Drones and Acoustic and Visual Sensors in Remote Detection and Localization of Objects and Events

  • Piotr Szczuko, Grzegorz Szwoch, Maciej Szczodrak, Jozef Kotus, and Andrzej Czyzewski. Zastosowania dronow i sensorow wizyjnych i akustycznych do zdalnej detekcji i lokalizacji obiektow i zdarzen (Application of Drones and Acoustic and Visual Sensors in Remote Detection and Localization of Objects and Events). In Krajowe Sympozjum Telekomunikacji i Teleinformatyki (KSTiT 2016), Gliwice, Poland, 2016.
    [BibTeX]
    @InProceedings{2016-09-SZCZUKOb,
    author = {Piotr Szczuko and Grzegorz Szwoch and Maciej Szczodrak and Jozef Kotus and Andrzej Czyzewski},
    title = {{Zastosowania dronow i sensorow wizyjnych i akustycznych do zdalnej detekcji i lokalizacji obiektow i zdarzen (Application of Drones and Acoustic and Visual Sensors in Remote Detection and Localization of Objects and Events)}},
    booktitle = {{Krajowe Sympozjum Telekomunikacji i Teleinformatyki (KSTiT 2016)}},
    address = {Gliwice, Poland},
    date = {2016-09-26/2016-09-28},
    year = {2016}
    }

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Distributed Visual Processing

Distributed Visual Processing

  • Andrea Cavallaro. Distributed Visual Processing. Tutorial at IEEE International Conference on Image Processing, 2016.
    [BibTeX] [Abstract]

    This tutorial will cover fundamental aspects, challenges and current solutions in distributed visual processing using networks of self-organising wired and wireless smart cameras, with applications in robotics, security and the Internet-of-Things. The tutorial sets forth the state-of-the-art in state estimation and coalition formation for distributed smart cameras. The tutorial will discuss and demonstrate the latest algorithms with a unified and comprehensive coverage. Using practical examples and illustration as support, the tutorial will introduce the participants in a discussion of the advantages and the limitations of traditional and modern approaches for synchronisation, distributed estimation and distributed processing for decision making and actuation in camera networks. Recent methods will be presented that allow cameras to move and to interact locally forming coalitions adaptively in order to provide coordinated decisions under resource and physical constraints. The tutorial will also discuss how cameras may learn to improve their performance. I will conclude the tutorial by introducing a collection of software resources to help the attendees develop and test distributed signal processing algorithms for wireless smart cameras.

    @Misc{2016-09-CAVALLAROb,
    author = {Andrea Cavallaro},
    title = {{Distributed Visual Processing}},
    howpublished = {Tutorial at IEEE International Conference on Image Processing},
    date = {2016-09-25/2016-09-28},
    year = {2016},
    address = {Phoenix, USA},
    abstract = {This tutorial will cover fundamental aspects, challenges and current solutions in distributed visual processing using networks of self-organising wired and wireless smart cameras, with applications in robotics, security and the Internet-of-Things. The tutorial sets forth the state-of-the-art in state estimation and coalition formation for distributed smart cameras. The tutorial will discuss and demonstrate the latest algorithms with a unified and comprehensive coverage. Using practical examples and illustration as support, the tutorial will introduce the participants in a discussion of the advantages and the limitations of traditional and modern approaches for synchronisation, distributed estimation and distributed processing for decision making and actuation in camera networks. Recent methods will be presented that allow cameras to move and to interact locally forming coalitions adaptively in order to provide coordinated decisions under resource and physical constraints. The tutorial will also discuss how cameras may learn to improve their performance. I will conclude the tutorial by introducing a collection of software resources to help the attendees develop and test distributed signal processing algorithms for wireless smart cameras.}
    }

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Performance evaluation of the parallel object tracking algorithm employing the particle filter

Performance evaluation of the parallel object tracking algorithm employing the particle filter

  • Grzegorz Szwoch. Performance evaluation of the parallel object tracking algorithm employing the particle filter. In 20th IEEE Conference SPA 2016, Signal Processing, Algorithms, Architectures, Arrangements, and Applications, Poznan, Poland, 2016. doi:10.1109/SPA.2016.7763598
    [BibTeX]
    @InProceedings{2016-09-SZWOCH,
    author = {Grzegorz Szwoch},
    title = {{Performance evaluation of the parallel object tracking algorithm employing the particle filter}},
    booktitle = {{20th IEEE Conference SPA 2016, Signal Processing, Algorithms, Architectures, Arrangements, and Applications}},
    date = {2016-09-21/2016-09-23},
    year = {2016},
    doi = {10.1109/SPA.2016.7763598},
    address = {Poznan, Poland}
    }

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