Interactive Background blurring focal length effect

Outline Introduction Related Work Method Artifacts Applications

消費型數位相機 NIKON E4300 (2003) 數位單眼相機 NIKON D90(2008)

Introduction Real world Photo plane Depth of field Photo plane Real light Circle of Confusion Out of focus

Introduction Real light Circle of Confusion - Readability range Focus plane Photo plane Out of focus – blur range Depth of field Real light Circle of Confusion - Readability range Focus plane Photo plane Out of focus – blur range Depth of field

Introduction Real world Photo plane Low DOF

Refocusing : Active Refocusing of Images and Videos [siggraph07] Depth hint: active project light Blur kernel: Gaussian blur Related Work 7

8 Image and Depth from a Conventional Camera with a Coded Aperture [siggraph07]

9 Related Work Single Image Dehazing [siggraph08] Radiative transport equation

Related Work Tip of those work ◦ Depth map  Hint source  Active hint (light, lens pattern, drag) ◦ Application  All-focus picture  Movie  3D model Blur effect Depth information Special Effect (3D reconstruct) Other Applications Special Effect (3D reconstruct) Other Applications Depth information Blur effect

Method Load image from file Segment Lazy snapping Depth map 3D retangle Blur circle diameter Camera setting Blur result Defocus blur Vanish stroke Mean shift Save image to file Soft Color segmentation Face detection ation

Method Segment ◦ Lazy snapping ◦ Face detection ◦ Mean shift ◦ SoftColor segmentation Resize 20% Do graph cut Segment Map User Stroke

Method Depth map ◦ Vanish Box Depth Map Vanish Box

Method Blur circle diameter ◦ Circle of confusion blur disk diameter b of a detail at distance x d from the subject ◦ Bokeh Blur circle diameter Segment Map Depth Map Camera setting 光圈大小 光圈形狀 鏡頭焦距 倍率 焦距 ( 物距 ) 散景程度 光圈大小 光圈形狀 鏡頭焦距 倍率 焦距 ( 物距 ) 散景程度

Method Blur result Coc map Segment Map Blur Result pixel(i,j) -> cicle (i,j,d) * weight(i,j) Cicle 越分散強度越弱 原來的亮度值越高強度越強 Weight = pixel 亮度 / cicle 面積 最後再做 normalize Bokeh 的結果就是 weight 溢位

Segment 解決方法： 加入 mean shift 把 lazy snapping 的 result 當 作 color segmentation 的 initial data 解決方法： 加入 mean shift 把 lazy snapping 的 result 當 作 color segmentation 的 initial data Artifacts (PART1) Lazy snapping result 理想狀態 Color histogram

Artifacts (PART2) Depth part ◦ Depth of Each Pixel / depth of Each Object 解決方法： 加入 mean shift 當作 object 的依據 解決方法： 加入 mean shift 當作 object 的依據

Artifacts (PART3) Blur kernel 比普通的 Gaussian blur 更接近光學結果 缺點：慢 Gaussian blur Defocus blur Defocus blur + Bokeh

Applications 呈現方法： ◦ MOVIE ? ◦ PHOTO ◦ Subject test…

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