公开(公告)号：US09307222B1

公开(公告)日：2016-04-05

申请号：US14577792

申请日：2014-12-19

Applicant: Adobe Systems Incorporated

Inventor： Huixuan Tang ,  Scott Cohen ,  Stephen Schiller ,  Brian Price

IPC: H04N5/232 ,  H04N13/00

CPC classification number: H04N13/128 ,  G06K9/4661 ,  G06K9/6215 ,  G06K2009/4666 ,  G06T5/003 ,  G06T5/50 ,  G06T7/571 ,  G06T2207/10016 ,  G06T2207/10028 ,  G06T2207/10148 ,  G06T2207/20048 ,  H04N1/387 ,  H04N5/2226 ,  H04N5/23212 ,  H04N5/23222 ,  H04N5/2329 ,  H04N5/2351 ,  H04N5/2355 ,  H04N5/33 ,  H04N13/271 ,  H04N17/002 ,  H04N2013/0081 ,  H04N2213/003

Abstract: Systems and methods are disclosed for identifying image capture instructions for capturing images that may be used to generate quality depth maps. In some examples, the image capture instructions are generated by predictively determining in a scene-independent manner configuration settings to be used by a camera to capture a minimal quantity of images for generating the quality depth map. The image capture instructions may thus indicate a quantity of images to be captured and the aperture and focus settings to be used when capturing the images. The image capture instructions may be determined based in part on a distance estimate, camera calibration information and a predetermined range of optimal blur radii. The range of optimal blur radii ensures that there will be sufficient depth information for generating a depth map of a particular quality from the yet-to-be-captured images.

Abstract translation: 公开了用于识别用于捕获可用于生成质量深度图的图像的图像捕获指令的系统和方法。 在一些示例中，通过以与场景无关的方式来预测性地确定要由相机使用的配置设置来捕获用于生成质量深度图的最小量的图像来生成图像捕获指令。 因此，图像拍摄指令可以指示要捕获的图像的数量以及在拍摄图像时要使用的光圈和聚焦设置。 图像捕获指令可以部分地基于距离估计，相机校准信息和最佳模糊半径的预定范围来确定。 最佳模糊半径的范围确保将有足够的深度信息用于从未被捕获的图像生成特定质量的深度图。

公开(公告)号：US09292926B1

公开(公告)日：2016-03-22

申请号：US14552332

申请日：2014-11-24

Applicant: Adobe Systems Incorporated

Inventor： Huixuan Tang ,  Scott Cohen ,  Stephen Schiller ,  Brian Price

IPC: H04N5/222 ,  H04N5/232 ,  G06T7/00 ,  G06T7/20 ,  H04N5/235 ,  H04N13/02 ,  H04N1/387

CPC classification number: H04N13/128 ,  G06K9/4661 ,  G06K9/6215 ,  G06K2009/4666 ,  G06T5/003 ,  G06T5/50 ,  G06T7/571 ,  G06T2207/10016 ,  G06T2207/10028 ,  G06T2207/10148 ,  G06T2207/20048 ,  H04N1/387 ,  H04N5/2226 ,  H04N5/23212 ,  H04N5/23222 ,  H04N5/2329 ,  H04N5/2351 ,  H04N5/2355 ,  H04N5/33 ,  H04N13/271 ,  H04N17/002 ,  H04N2013/0081 ,  H04N2213/003

Abstract: Depth maps are generated from two or more of images captured with a conventional digital camera from the same viewpoint using different configuration settings, which may be arbitrarily selected for each image. The configuration settings may include aperture and focus settings and/or other configuration settings capable of introducing blur into an image. The depth of a selected image patch is evaluated over a set of discrete depth hypotheses using a depth likelihood function modeled to analyze corresponding images patches convolved with blur kernels using a flat prior in the frequency domain. In this way, the depth likelihood function may be evaluated without first reconstructing an all-in-focus image. Blur kernels used in the depth likelihood function and are identified from a mapping of depths and configuration settings to the blur kernels. This mapping is determined from calibration data for the digital camera used to capture the two or more images.