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ROAM : A Rich Object Appearance Model with Application to Rotoscoping

Rotoscoping, the detailed delineation of scene elements through a video shot, is a painstaking task of tremendous importance in professional post-production pipelines. While pixel-wise segmentation techniques can help for this task, professional rotoscoping tools rely on parametric curves that offer the artists a much better interactive control on the definition, editing and manipulation of the segments of interest. Sticking to this prevalent rotoscoping paradigm, we propose a novel framework to capture and track the visual aspect of an arbitrary object in a scene, given a first closed outline of this object. This model combines a collection of local
foreground/background appearance models spread along the outline, a global appearance model of the enclosed object and a set of distinctive foreground landmarks. The structure of this rich appearance model allows simple initialization, efficient iterative optimization with exact minimization at each step, and on-line adaptation in videos. We demonstrate qualitatively and quantitatively the merit of this framework through comparisons with tools based on either dynamic segmentation with a closed curve or pixel-wise binary labelling.

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Informasi Detail

Judul Seri

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE; Vol.42 No.8 August 2020

No. Panggil

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Penerbit

: .,

Deskripsi Fisik

p. 1996 - 2010

Bahasa

English

ISBN/ISSN

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Klasifikasi

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Tipe Isi

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Tipe Media

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Tipe Pembawa

-

Edisi

-

Subjek

DYNAMIC PROGRAMMING
PROBABILISTIC GRAPHICAL MODELS
VIDEO SEGMENTATION
ROTOSCOPING
TRIMAPS
VIDEO ALPHA-MATTING

Info Detail Spesifik

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Pernyataan Tanggungjawab

Juan-Manuel Perez-Rua, Ondrej Miksik, Tomas Crivelli, Patrick Bouthemy, Philip H.S. Torr, Patrick Perez

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