Publication | Open Access
Synthetic depth-of-field with a single-camera mobile phone
180
Citations
40
References
2018
Year
Scene AnalysisEngineeringField RoboticsDepth MapDense Depth MapImage AnalysisComputational ImagingComputational PhotographySynthetic Depth-of-fieldPerson Segmentation NetworkGeometric ModelingLight Field ImagingMachine VisionComputer ScienceShallow Depth-of-fieldDeep LearningComputer VisionScene UnderstandingScene Modeling
Shallow depth-of-field is commonly used by photographers to isolate a subject from a distracting background. However, standard cell phone cameras cannot produce such images optically, as their short focal lengths and small apertures capture nearly all-in-focus images. We present a system to computationally synthesize shallow depth-of-field images with a single mobile camera and a single button press. If the image is of a person, we use a person segmentation network to separate the person and their accessories from the background. If available, we also use dense dual-pixel auto-focus hardware, effectively a 2-sample light field with an approximately 1 millimeter baseline, to compute a dense depth map. These two signals are combined and used to render a defocused image. Our system can process a 5.4 megapixel image in 4 seconds on a mobile phone, is fully automatic, and is robust enough to be used by non-experts. The modular nature of our system allows it to degrade naturally in the absence of a dual-pixel sensor or a human subject.
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