Natural video matting using camera arrays

Joshi, Neel; Matusik, Wojciech; Avidan, Shai

doi:10.1145/1179352.1141955

Cited by 46 publications

(46 citation statements)

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“…Sun et al [16] propose a method to estimate matte from well-aligned flash/non-flash image pairs. Joshi et al [17] present a video matting system using a camera array. These systems are only applicable with very restricted settings and cannot be easily generalized to handle a wide range of real-world examples.…”

Section: Multi-image Mattingmentioning

confidence: 99%

Confidence-driven image co-matting

Wang

Xia

Guo

et al. 2014

Computers & Graphics

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Section: Multi-image Mattingmentioning

confidence: 99%

Confidence-driven image co-matting

Wang

Xia

Guo

et al. 2014

Computers & Graphics

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“…Most of the existing systems need ʺmanualʺ adjustment of the focus plane. In SIGRAPH2006, Joshi et al [15] took the lead on presenting a camera array ʺautofocusʺ algorithm. Their approach is similar to the contrast measurement of single camera AF, where a camera varies its focus and picks the setting that gives the strongest gradients in pre-defined regions.…”

Section: Camera Array Autofocusmentioning

confidence: 99%

Exploiting Loops in the Camera Array for Automatic Focusing Depth Estimation

Yang

Zhang

et al. 2013

International Journal of Advanced Robotic Systems

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Autofocus is a fundamental and key problem for modern imaging sensor design. Although this problem has been well studied in single camera literature, unfortunately, little research has been done on large-scale camera arrays. Most of the existing synthetic aperture imaging systems still need to manually select the optimal focus plane when an object moves. Unlike the conventional autofocus method, which sweeps the focus plane to find the maximal contrast, we present a novel optimization framework to handle the above challenges. In particular, we formulate the camera array autofocus problem as a constrained optimization problem by minimizing the temporal and spatial correspondences error subject to global loop constraint. Then this problem is relaxed as a quadratic program and solved using sequential quadratic programming. The experimental results show that the proposed method achieves a better performance compared with the results of traditional methods. To the best of our knowledge, our proposed method is the first optimization framework for solving camera array autofocus problem and it is of great importance to improve the performance of the existing synthetic aperture imaging system.

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“…The alpha matte is calculated by solving an error minimization problem, which takes several minutes per frame. Automatic video matting can also be achieved using a camera array (Joshi et al 2006). The images captured are aligned so that the variance of pixels re-projected from the foreground is minimized and the variance of pixels reprojected from the background is maximized.…”

Section: Video Mattingmentioning

confidence: 99%

Automatic Real-Time Video Matting Using Time-of-Flight Camera and Multichannel Poisson Equations

et al. 2011

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This paper presents an automatic real-time video matting system. The proposed system consists of two novel components. In order to automatically generate trimaps for live videos, we advocate a Time-of-Flight (TOF) camerabased approach to video bilayer segmentation. Our algorithm combines color and depth cues in a probabilistic fusion framework. The scene depth information returned by the TOF camera is less sensitive to environment changes, which makes our method robust to illumination variation, dynamic background and camera motion. For the second step, we perform alpha matting based on the segmentation Electronic supplementary material The online version of this article (doi:10.1007/s11263-011-0471-x) contains supplementary material, which is available to authorized users. result. Our matting algorithm uses a set of novel Poisson equations that are derived for handling multichannel color vectors, as well as the depth information captured. Realtime processing speed is achieved through optimizing the algorithm for parallel processing on graphics hardware. We demonstrate the effectiveness of our matting system on an extensive set of experimental results.

show abstract

Natural video matting using camera arrays

Cited by 46 publications

References 0 publications

Confidence-driven image co-matting

Confidence-driven image co-matting

Exploiting Loops in the Camera Array for Automatic Focusing Depth Estimation

Automatic Real-Time Video Matting Using Time-of-Flight Camera and Multichannel Poisson Equations

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