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SIGGRAPH ASIA 2014 Technical Paper Fast Forward

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Presentation on theme: "SIGGRAPH ASIA 2014 Technical Paper Fast Forward"— Presentation transcript:

1 SIGGRAPH ASIA 2014 Technical Paper Fast Forward
Digital Photography

2 Digital Photography FlexISP: A Flexible Camera Image Processing Framework Fast Burst Images Denoising Spatial-spectral Encoded Compressive Hyperspectral Imaging Mirror Mirror: Crowdsourcing Better Portraits

3 Digital Photography FlexISP: A Flexible Camera Image Processing Framework Fast Burst Images Denoising Spatial-spectral Encoded Compressive Hyperspectral Imaging Mirror Mirror: Crowdsourcing Better Portraits

4 FlexISP: A Flexible Camera Image Processing Framework
Author Jing Liu (UC Santa Cruz), Felix Heide (UBC), Wolfgang Heidrich (KAUST), Markus Steinberger (TU Graz), Yun-Ta Tsai (NVIDIA), Karen Egiazarian (TUT), Jan Kautz (NVIDIA), Mushfiqur Rouf (UBC), Kari Pulli (NVIDIA) Dawid Pająk (NVIDIA), Dikpal Reddy (NVIDIA), Orazio Gallo (NVIDIA),

5 FlexISP: A Flexible Camera Image Processing Framework
Abstract 傳統的 camera pipelines 每一個 stage 都是處理不同的問題，可是每一個 stage 都是吃上一個 stage 的 output 當做 input ，不是拿最初的 original sensor raw data 拿來做處理，所以會有累積的 error 一直傳下去。 這篇 paper 介紹他們做的一個 end-to-end system 和 framework ，從 camera 吃進來 raw data 後，透過一些預處理等等的方式，加上他選擇使用一步驟的 global energy object function，就可以把傳統 pipeline 要解決的問題一口氣找出 optimal solution。

6 FlexISP: A Flexible Camera Image Processing Framework
Abstract 傳統的 camera pipelines 每一個 stage 都是處理不同的問題，可是每一個 stage 都是吃上一個 stage 的 output 當做 input ，不是拿最初的 original sensor raw data 拿來做處理，所以會有累積的 error 一直傳下去。 這篇 paper 介紹他們做的一個 end-to-end system 和 framework ，從 camera 吃進來 raw data 後，透過一些預處理等等的方式，加上他選擇使用一步驟的 global energy object function，就可以把傳統 pipeline 要解決的問題一口氣找出 optimal solution。

7 FlexISP: A Flexible Camera Image Processing Framework
Abstract 傳統的 camera pipelines 每一個 stage 都是處理不同的問題，可是每一個 stage 都是吃上一個 stage 的 output 當做 input ，不是拿最初的 original sensor raw data 拿來做處理，所以會有累積的 error 一直傳下去。 這篇 paper 介紹他們做的一個 end-to-end system 和 framework ，從 camera 吃進來 raw data 後，透過一些預處理等等的方式，加上他選擇使用一步驟的 global energy object function，就可以把傳統 pipeline 要解決的問題一口氣找出 optimal solution。

8 FlexISP: A Flexible Camera Image Processing Framework
Video

9 FlexISP: A Flexible Camera Image Processing Framework
Conclusion FlexISP, a framework and a system that replaces the traditional image processing pipeline. The image formation model is expressed as a single objective function, which is solved using a proximal operator framework.

10 Digital Photography FlexISP: A Flexible Camera Image Processing Framework Fast Burst Images Denoising Spatial-spectral Encoded Compressive Hyperspectral Imaging Mirror Mirror: Crowdsourcing Better Portraits

11 Fast Burst Images Denoising
Author Ziwei Liu (The Chinese University of Hong Kong) Lu Yuan (Microsoft Research) Xiaoou Tang (The Chinese University of Hong Kong) Matt Uyttendaele (Microsoft Research Technologies) Jian Sun (Microsoft Research)

12 Fast Burst Images Denoising
Abstract a fast denoising method that produces a clean image from a burst of noisy images. This paper presents a fast denoising method that produces a clean image from a burst of noisy images. We accelerate alignment of the images by introducing a lightweight camera motion representation called homography flow. The aligned images are then fused to create a denoised output with rapid per-pixel operations in temporal and spatial domains. To handle scene motion during the capture, a mechanism of selecting consistent pixels for temporal fusion is proposed to “synthesize” a clean, ghost-free image, which can largely reduce the computation of tracking motion between frames. Combined with these efficient solutions, our method runs several orders of magnitude faster than previous work, while the denoising quality is comparable. A smartphone prototype demonstrates that our method is practical and works well on a large variety of real examples.

13 Fast Burst Images Denoising
Video

14 Fast Burst Images Denoising
Limitations motion blur caused by dynamic objects appears on a majority of frames (more than half of all frames).

15 Fast Burst Images Denoising
Conclusion a fast denoising method that produces a clean image from a burst of noisy images. This paper presents a fast denoising method that produces a clean image from a burst of noisy images. We accelerate alignment of the images by introducing a lightweight camera motion representation called homography flow. The aligned images are then fused to create a denoised output with rapid per-pixel operations in temporal and spatial domains. To handle scene motion during the capture, a mechanism of selecting consistent pixels for temporal fusion is proposed to “synthesize” a clean, ghost-free image, which can largely reduce the computation of tracking motion between frames. Combined with these efficient solutions, our method runs several orders of magnitude faster than previous work, while the denoising quality is comparable. A smartphone prototype demonstrates that our method is practical and works well on a large variety of real examples.

16 Digital Photography FlexISP: A Flexible Camera Image Processing Framework Fast Burst Images Denoising Spatial-spectral Encoded Compressive Hyperspectral Imaging Mirror Mirror: Crowdsourcing Better Portraits

17 Spatial-spectral Encoded Compressive Hyperspectral Imaging
Author Xing Lin (Tsinghua University) Yebin Liu (Tsinghua University) Jiamin Wu (Tsinghua University) Qionghai Dai (Tsinghua University) Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP), Tsinghua University

18 Spatial-spectral Encoded Compressive Hyperspectral Imaging
Abstract

19 Spatial-spectral Encoded Compressive Hyperspectral Imaging
Video (dead now)

20 Spatial-spectral Encoded Compressive Hyperspectral Imaging

21 Spatial-spectral Encoded Compressive Hyperspectral Imaging

22 Spatial-spectral Encoded Compressive Hyperspectral Imaging

23 Spatial-spectral Encoded Compressive Hyperspectral Imaging

24 Spatial-spectral Encoded Compressive Hyperspectral Imaging

25 Spatial-spectral Encoded Compressive Hyperspectral Imaging

26 Spatial-spectral Encoded Compressive Hyperspectral Imaging

27 Spatial-spectral Encoded Compressive Hyperspectral Imaging
Summary

28 Digital Photography FlexISP: A Flexible Camera Image Processing Framework Fast Burst Images Denoising Spatial-spectral Encoded Compressive Hyperspectral Imaging Mirror Mirror: Crowdsourcing Better Portraits

29 Mirror Mirror: Crowdsourcing Better Portraits
Author Jun-Yan Zhu (University of California, Berkeley) Aseem Agarwala (Adobe) Alexei A. Efros (University of California, Berkeley) Eli Shechtman (Adobe) Jue Wang (Adobe)

30 Mirror Mirror: Crowdsourcing Better Portraits
Abstract

31 Mirror Mirror: Crowdsourcing Better Portraits

32 Mirror Mirror: Crowdsourcing Better Portraits

33 Mirror Mirror: Crowdsourcing Better Portraits

34 Mirror Mirror: Crowdsourcing Better Portraits
Video

35 Mirror Mirror: Crowdsourcing Better Portraits
Conclusion

36 Digital Photography FlexISP: A Flexible Camera Image Processing Framework Fast Burst Images Denoising Spatial-spectral Encoded Compressive Hyperspectral Imaging Mirror Mirror: Crowdsourcing Better Portraits

37

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