[image 02977] 再送: 講演会(4/27)のご案内

Akihiro Sugimoto sugimoto @ nii.ac.jp
2018年 4月 26日 (木) 12:18:05 JST


皆様

既にご案内している下記の講演会が明日に迫りましたので、再度ご案内
させていただきます。多数のご参加をお待ちしています。

杉本

On Mon, 09 Apr 2018 14:45:27 +0900
Akihiro Sugimoto <sugimoto @ nii.ac.jp> wrote:

> 皆様
> 
> 下記の講演会2件を開催しますので、ふるってご参加ください。事前登録、参加
> 費ともに不要です。
> 
> 杉本
> 
> ---------
> 日時: 4月27日(金) 16:00〜18:15
> 場所: 国立情報学研究所 19F 1901&1902号室
>     (東京都千代田区一ツ橋2-1-2)
>      https://www.nii.ac.jp/about/access/
> 
> ----------------------- talk #1 -----------------------------
> Speaker:  Dr. Zuzana Kukelova
>              Dept. of Cybernetics
>                 Czech Technical University in Prague
>              http://kukelova.weebly.com
> 
> Title: 
> Fast Grobner basis solvers for computer vision problems
> 
> Abstract: 
> Many problems in computer vision, but also in other field such as robotics,
> control design or economics, can be formulated using systems of polynomial
> equations.
> For computer vision problems, general algorithms for solving polynomial
> systems cannot be efficiently applied. The reasons are twofold - computer
> vision and robotic applications usually require real time solutions, or
> they often solve systems of polynomial equations for millions of different
> instances. Several approaches based on algebraic geometry have been
> recently proposed for the design of very efficient algorithms (solvers)
> that solve specific classes of systems of polynomial equations.
> In this talk we will briefly discuss such method for creating efficient
> solvers of systems of polynomial equations. This method is based on Grobner
> bases and it uses the structure of the system of polynomial equations
> representing a particular problem to design an efficient specific solver
> for this problem. We will discuss several approaches for improving the
> efficiency of the final solvers. We will also introduce the automatic
> generator of Grobner basis solvers which could be used even by non-experts
> to efficiently solve problems resulting in systems of polynomial
> equations. Finally, we will demonstrate the usefulness of the approach by
> presenting new, efficient and numerical stable solutions to several
> important computer vision problems and problems from robotics.
> 
> ------------------- talk #2 -----------------------------
> Speaker:  Prof. Tomas Pajdla 
>                 Czech Institute of Informatics, Robotics and Cybernetics,
>                 Czech Technical University in Prague
>                 http://people.ciirc.cvut.cz/~pajdla/
> 
> Title: On the Two-View Geometry of Unsynchronized Cameras
> 
> Abstract:
> We will present a method for simultaneously estimating camera geometry 
> and time  shift from video sequences from multiple unsynchronized
> cameras. We estimate fundamental matrices and homographies and the
> unknown time shift between images. We use minimal correspondence sets
> (eight for fundamental matrix and four and a half for homography), and
> hence our approach is suitable for robust estimation using RANSAC.
> Furthermore, we present an iterative algorithm that extends the
> applicability on sequences which are significantly unsynchronized, finding
> the correct time shift up to several seconds. We evaluate the
> methods on synthetic and wide range of real world datasets and the
> results show a broad applicability to the problem of camera synchronization.
> 
> --------------------
> 
> 
> 
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