Monthly Archives: March 2015

MTTV – An Interactive Trajectory Visualization and Analysis Tool

MTTV – An Interactive Trajectory Visualization and Analysis Tool

  • Fabio Poiesi and Andrea Cavallaro. MTTV – An Interactive Trajectory Visualization and Analysis Tool. In Proceedings of Information Visualization Theory and Applications (IVAPP), pages 157-162, Berlin, Germany, 2015.
    [BibTeX] [Abstract]

    We present an interactive visualizer that enables the exploration, measurement, analysis and manipulation of trajectories. Trajectories can be generated either automatically by multi-target tracking algorithms or manually by human annotators. The visualizer helps understanding the behavior of targets, correcting tracking results and quantifying the performance of tracking algorithms. The input video can be overlaid to compare ideal and estimated target locations. The code of the visualizer (C++ with openFrameworks) is open source.

    @InProceedings{2015-03-POIESI,
    author = {Fabio Poiesi and Andrea Cavallaro},
    title = {{MTTV - An Interactive Trajectory Visualization and Analysis Tool}},
    booktitle = {{Proceedings of Information Visualization Theory and Applications (IVAPP)}},
    date = {2015-03-11/2015-03-14},
    address = {Berlin, Germany},
    pages = {157-162},
    abstract = {We present an interactive visualizer that enables the exploration, measurement, analysis and manipulation of trajectories. Trajectories can be generated either automatically by multi-target tracking algorithms or manually by human annotators. The visualizer helps understanding the behavior of targets, correcting tracking results and quantifying the performance of tracking algorithms. The input video can be overlaid to compare ideal and estimated target locations. The code of the visualizer (C++ with openFrameworks) is open source.},
    year = {2015}
    }

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Visualization of Pareto front approximations in evolutionary multiobjective optimization: A critical review and the prosection method

Visualization of Pareto front approximations in evolutionary multiobjective optimization: A critical review and the prosection method

  • Tea Tušar and Bogdan Filipič. Visualization of Pareto front approximations in evolutionary multiobjective optimization: A critical review and the prosection method. IEEE Transactions on Evolutionary Computation, 19(2):225-245, 2015. doi:10.1109/TEVC.2014.2313407
    [BibTeX] [Abstract]

    In evolutionary multiobjective optimization, it is very important to be able to visualize approximations of the Pareto front (called approximation sets) that are found by multiobjective evolutionary algorithms. While scatter plots can be used for visualizing 2-D and 3-D approximation sets, more advanced approaches are needed to handle four or more objectives. This paper presents a comprehensive review of the existing visualization methods used in evolutionary multiobjective optimization, showing their outcomes on two novel 4-D benchmark approximation sets. In addition, a visualization method that uses prosection (projection of a section) to visualize 4-D approximation sets is proposed. The method reproduces the shape, range, and distribution of vectors in the observed approximation sets well and can handle multiple large approximation sets while being robust and computationally inexpensive. Even more importantly, for some vectors, the visualization with prosections preserves the Pareto dominance relation and relative closeness to reference points. The method is analyzed theoretically and demonstrated on several approximation sets.

    @article{2015-03-TUSAR,
    title = {{Visualization of Pareto front approximations in evolutionary multiobjective optimization: A critical review and the prosection method}},
    author = {Tea Tu\v{s}ar and Bogdan Filipi\v{c}},
    journal = {{IEEE Transactions on Evolutionary Computation}},
    volume = {19},
    number = {2},
    pages = {225-245},
    year = {2015},
    date = {2015-04},
    abstract = {In evolutionary multiobjective optimization, it is very important to be able to visualize approximations of the Pareto front (called approximation sets) that are found by multiobjective evolutionary algorithms. While scatter plots can be used for visualizing 2-D and 3-D approximation sets, more advanced approaches are needed to handle four or more objectives. This paper presents a comprehensive review of the existing visualization methods used in evolutionary multiobjective optimization, showing their outcomes on two novel 4-D benchmark approximation sets. In addition, a visualization method that uses prosection (projection of a section) to visualize 4-D approximation sets is proposed. The method reproduces the shape, range, and distribution of vectors in the observed approximation sets well and can handle multiple large approximation sets while being robust and computationally inexpensive. Even more importantly, for some vectors, the visualization with prosections preserves the Pareto dominance relation and relative closeness to reference points. The method is analyzed theoretically and demonstrated on several approximation sets.},
    doi = {10.1109/TEVC.2014.2313407}
    }

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Social Cameras

Social Cameras

  • Andrea Cavallaro. Social Cameras. Keynote lecture at International Conference on Computer Vision, Imaging and Computer Graphics, 2015.
    [BibTeX] [Abstract]

    The pervasiveness of amateur wearable and handheld cameras has been revolutionizing the way private and public events are captured and shared. This explosion of content from social cameras and their shared user-generated videos offers the opportunity for new ways of analysing and timely reporting stories that range from music concerts and sports events to disaster scenes and protests. However, this large amount of increasingly available videos and their varying quality makes the selection and editing very difficult thus strongly limiting the opportunity to harvest the value of these user-generated videos. This talk will cover audio-visual methods for the automated grouping and synchronisation of multi-view user-generated videos in unconstrained scenarios. I will present ways to align these videos on a global timeline and show how to automatically edit them to produce a coherent final cut.

    @Misc{2015-03-CAVALLARO,
    author = {Andrea Cavallaro},
    title = {{Social Cameras}},
    howpublished = {Keynote lecture at International Conference on Computer Vision, Imaging and Computer Graphics},
    date = {2015-03-11},
    address = {Berlin, Germany},
    year = {2015},
    abstract = {The pervasiveness of amateur wearable and handheld cameras has been revolutionizing the way private and public events are captured and shared. This explosion of content from social cameras and their shared user-generated videos offers the opportunity for new ways of analysing and timely reporting stories that range from music concerts and sports events to disaster scenes and protests. However, this large amount of increasingly available videos and their varying quality makes the selection and editing very difficult thus strongly limiting the opportunity to harvest the value of these user-generated videos. This talk will cover audio-visual methods for the automated grouping and synchronisation of multi-view user-generated videos in unconstrained scenarios. I will present ways to align these videos on a global timeline and show how to automatically edit them to produce a coherent final cut.}
    }

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