کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
412047 679608 2015 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Automatic stereoscopic video generation based on virtual view synthesis
ترجمه فارسی عنوان
نسل های ویدئویی اتوماتیک بر اساس سنتز دید مجازی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

Automatically synthesizing 3D content from a causal monocular video has become an important problem. Previous works either use no geometry information, or rely on precise 3D geometry information. Therefore, they cannot obtain reasonable results if the 3D structure in the scene is complex, or noisy 3D geometry information is estimated from monocular videos. In this paper, we present an automatic and robust framework to synthesize stereoscopic videos from casual 2D monocular videos. First, 3D geometry information (e.g., camera parameters, depth map) are extracted from the 2D input video. Then a Bayesian-based View Synthesis (BVS) approach is proposed to render high-quality new virtual views for stereoscopic video to deal with noisy 3D geometry information. Extensive experiments on various videos demonstrate that BVS can synthesize more accurate views than other methods, and our proposed framework also outperforms state-of-the-art automatic 2D-to-3D conversion approaches.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 151, Part 2, 5 March 2015, Pages 654–662
نویسندگان
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