Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Konferenzbeitrag

Scene-aware Video Stabilization by Visual Fixation

MPG-Autoren
/persons/resource/persons44872

Kurz,  Christian
Computer Graphics, MPI for Informatics, Max Planck Society;
International Max Planck Research School, MPI for Informatics, Max Planck Society;

Thromählen,  Thorsten
Max Planck Society;

/persons/resource/persons45449

Seidel,  Hans-Peter       
Computer Graphics, MPI for Informatics, Max Planck Society;

Externe Ressourcen
Es sind keine externen Ressourcen hinterlegt
Volltexte (beschränkter Zugriff)
Für Ihren IP-Bereich sind aktuell keine Volltexte freigegeben.
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte in PuRe verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Kurz, C., Thromählen, T., & Seidel, H.-P. (2009). Scene-aware Video Stabilization by Visual Fixation. In The 6th European Conference for Visual Media Production (CVMP2009) (pp. XX-XX). Address, Invalid: IEEE Computer Society.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-000F-19DD-6
Zusammenfassung
Visual fixation is employed by humans and some animals to keep a specific 3D location at the center of the visual gaze. Inspired by this phenomenon in nature, this paper explores the idea to transfer this mechanism to the context of video stabilization for a hand-held video camera. A novel approach is presented that stabilizes a video by fixating on automatically extracted 3D target points. This approach is different from existing automatic solutions that stabilize the video by smoothing. To determine the 3D target points, the recorded scene is analyzed with a state-of-the-art structure-from-motion algorithm, which estimates camera motion and reconstructs a 3D point cloud of the static scene objects. Special algorithms are presented that search either virtual or real 3D target points, which back-project close to the center of the image for as long a period of time as possible. The stabilization algorithm then transforms the original images of the sequence so that these 3D target points are kept exactly in the center of the image, which, in case of real 3D target points, produces a perfectly stable result at the image center. The approach is evaluated on a variety of videos taken with a hand-held camera in natural scenes.