Monthly Archives: October 2016

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}
    }

Posted in Dissemination | Leave a comment
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.}
    }

Posted in Dissemination | Leave a comment
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}
    }

Posted in Dissemination | Leave a comment
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.}
    }

Posted in Dissemination | Leave a comment
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}
    }

Posted in Dissemination | Leave a comment