Dense View Interpolation on Mobile Devices Using Focal Stacks

Sakurikar, Parikshit; Narayanan, P. J.

doi:10.1109/cvprw.2014.26

Cited by 7 publications

(4 citation statements)

References 8 publications

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“…Kodama and Kubota [6] extend this to a 3D filtering method for generating dense pin-hole views from novel viewpoints. Iterative computation of focal textures has also be used in our previous work to produce in-focus images for shallow focal stacks [7]. Nagahara et al [8] use a special camera to capture a focal sweep of the scene by aggregating the light on the sensor during relative translation between the sensor and the lens.…”

Section: Related Workmentioning

confidence: 99%

“…Smooth focus maps that consider neighborhood consistency can be generated using optimization methods such as Cost-Volume Filtering [17] or MRF labeling [18]. Iterative optimization methods can also be used to estimate smooth focus maps [7], [19]. Pertuz et al [20] analyze and compare several focus measures independently for the task of depth-from-focus.…”

Section: Related Workmentioning

confidence: 99%

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Geometric Scene Refocusing

Sakurikar¹,

Narayanan²

2020

Preprint

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An image captured with a wide-aperture camera exhibits a finite depth-of-field, with focused and defocused pixels. A compact and robust representation of focus and defocus helps analyze and manipulate such images. In this work, we study the fine characteristics of images with a shallow depth-of-field in the context of focal stacks. We present a composite measure for focus that is a combination of existing measures. We identify in-focus pixels, dual-focus pixels, pixels that exhibit bokeh and spatiallyvarying blur kernels between focal slices. We use these to build a novel representation that facilitates easy manipulation of focal stacks. We present a comprehensive algorithm for post-capture refocusing in a geometrically correct manner. Our approach can refocus the scene at high fidelity while preserving fine aspects of focus and defocus blur.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Geometric Scene Refocusing

Sakurikar¹,

Narayanan²

2020

Preprint

Self Cite

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“…However, all the cameras cannot focus the lens on specific focal points, nor sweep the lens. Sakurikar and Narayanan (2014) approached this problem by using camera autofocus so that the viewfinder was divided into 16 blocks and autofocus algorithm was pointed towards each block in order. Overly similar images were removed before registration.…”

Section: Preprint Submitted To Elseviermentioning

confidence: 99%

Increasing the capturing angle in print-cam robust watermarking

Pramila

Keskinarkaus

Seppänen

2018

Journal of Systems and Software

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It is nowadays more probable that a print media is captured and shared with a mobile phone than with a scanner. The reasons for photographing the print range from intention of copying the image to simply sharing an interesting add with friends. Watermarking offers a solution for carrying side information in the images, and if the watermarking method being used is robust to the print-cam process, the information can be read with a mobile phone camera. In this paper, we present a print-cam robust watermarking method that is also implemented on a mobile phone and evaluated with user tests. Especially, the lens focusing problem when the picture is captured in a wide angle with respect to the printout is addressed. The results show that the method is highly robust to capturing the watermark without errors in angles up to 60➦ with processing times that are acceptable for real-life applications.

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“…Focus sweep and focusing the lens to specific focal points is not available on all cameras as noted by Sakurikar et al [22]. On the other hand, most of the cameras on mobile phones have capabilities to direct the autofocus towards different locations on a scene.…”

Section: Related Workmentioning

confidence: 99%

Extracting watermarks from printouts captured with wide angles using computational photography

Pramila

Keskinarkaus

Takala

et al. 2016

Multimed Tools Appl

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Thus far the research of print-cam robust watermarking methods has focused on finding new methods for embedding and extracting the watermark. However, the capturing process itself, has been neglected in scientific research. In this paper, we propose a solution for the situation when the watermarked image has been captured in a wide angle and the depth of focus of the camera is not deep enough to capture the whole scene in-focus resulting in unfocused areas. The solution proposed here relies on a subfield of computational photography, namely all-in-focus imaging. All-in-focus images are generated by fusing multiple images from the same scene with different focus distances together, so that the object being photographed is fully in focus. Traditionally, the images to be fused are selected by hand from the focal stack or the whole stack is used for building the all-in-focus image. In mobile phone applications, computational resources are limited and using the full focal stack would result in long processing times and the manual selection of images would not be practical. In addition, we propose a method for optimizing the size of the focal stack and automatically selecting appropriate images for fusion. It is shown here that a watermark can still be recovered from the reconstructed all-in-focus image accurately.

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Dense View Interpolation on Mobile Devices Using Focal Stacks

Cited by 7 publications

References 8 publications

Geometric Scene Refocusing

Geometric Scene Refocusing

Increasing the capturing angle in print-cam robust watermarking

Extracting watermarks from printouts captured with wide angles using computational photography

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