Chen Sagiv

Chen Sagiv

Israel
13K‏ עוקבים מעל 500 קשרים

על אודות

Image processing researcher specializing in building algorithmic solutions to real life…

מאמרים מאת Chen

פעילות

הצטרפו עכשיו כדי לראות את כל פעילות

ניסיון

חינוך

ניסיון בהתנדבות

  • SagivTech גרפי

    co CEO

    SagivTech

    - 1 שנה

    חינוך

    I love Math and I love to teach. In the last 3 years I devote one afternoon a week for teaching high school children Math to final exams and supervise tech projects.

  • SagivTech גרפי

    Co CEO

    SagivTech

    -להציג 8 שנים 3 חודשים

    חינוך

    I teach Math in the children's boarding school Yuvalim in Kfar Saba. Great kids, Great team, Great feeling.

פרסומים

  • A Robust Estimation Method for Camera Calibration with Known Rotation

    Applied Mathematics

    Imagine that hundreds of video streams, taken by mobile phones during a rock concert, are uploaded to a server. One attractive application of such prominent dataset is to allow a user to create his own video with a deliberately chosen but virtual camera trajectory. In this paper we present algorithms for the main sub-tasks (spatial calibration, image interpolation) related to this problem. Calibration: Spatial calibration of individual video streams is one of the most basic tasks related to…

    Imagine that hundreds of video streams, taken by mobile phones during a rock concert, are uploaded to a server. One attractive application of such prominent dataset is to allow a user to create his own video with a deliberately chosen but virtual camera trajectory. In this paper we present algorithms for the main sub-tasks (spatial calibration, image interpolation) related to this problem. Calibration: Spatial calibration of individual video streams is one of the most basic tasks related to creating such a video. At its core, this requires to estimate the pairwise relative geometry of images taken by different cameras. It is also known as the relative pose problem [1], and is fundamental to many computer vision algorithms. In practice, efficiency and robustness are of highest relevance for big data applications such as the ones addressed in the EU-FET_SME project SceneNet. In this paper, we present an improved algorithm that exploits additional data from inertial sensors, such as accelerometer, magnetometer or gyroscopes, which by now are available in most mobile phones. Experimental results on synthetic and real data demonstrate the accuracy and efficiency of our algorithm. Interpolation: Given the calibrated cameras, we present a second algorithm that generates novel synthetic images along a predefined specific camera trajectory. Each frame is produced from two “neighboring” video streams that are selected from the data base. The interpolation algorithm is then based on the point cloud reconstructed in the spatial calibration phase and iteratively projects triangular patches from the existing images into the new view. We present convincing images synthesized with the proposed algorithm.

    אַחֵר הכותבים
    ראה פרסום
  • Edge detection and skeletonization using quantized localized Phase

    Proceedings of 17-th European Signal Processing Conference (EUSIPCO)

    אַחֵר הכותבים
    ראה פרסום

המלצות התקבל

עוד פעילות על ידי Chen

הצג Chen את הפרופיל המלא

  • ראה את מי שאתה מכיר במשותף
  • הכירו
  • צור קשר Chen ישירות
הצטרפו נוף הפרופיל המלא

פרופילים דומים אחרים

שמות אחרים Chen Sagiv ב Israel

הוסף כישורים חדשים עם קורסים אלה