Marc Levoy

Biographical sketch

Marc Levoy is the VMware Founders Professor of Computer Science (Emeritus) at Stanford University and a Vice President and Fellow at Adobe. In previous lives he worked on computer-assisted cartoon animation (1970s), volume rendering (1980s), 3D scanning (1990s), light field imaging (2000s), and computational photography (2010s). At Stanford he taught computer graphics, digital photography, and the science of art. At Google he launched Street View, co-designed the library book scanner, and led the team that created HDR+, Portrait Mode, and Night Sight for Pixel smartphones. These phones won DPReview's Innovation of the Year (2017 and 2018) and Smartphone Camera of the Year (2019), and Mobile World Congress's Disruptive Innovation Award (2019). Levoy's awards include Cornell University's Charles Goodwin Sands Medal for best undergraduate thesis (1976) and the ACM SIGGRAPH Computer Graphics Achievement Award (1996). He is an ACM Fellow (2007) and member of the National Academy of Engineering (2022).

• Details about the Sands Medal and my work in cartoon animation.
  
• Citation for the Computer Graphics Achievement Award.
  
• Details about the VMware Founders Professorship of Computer Science
• Computer Graphics Achievement Award.
  
• Curriculum vitae (PDF, no links to papers).
• National Academy of Engineering, and related Adobe interview.
• September 2022 article by CNET's Stephen Shankland, based on an interview a few weeks earlier.

My Stanford career

A volume rendering from my dissertation at UNC	The Stanford Bunny, from our 3D scanning repository	Volumetric scan and 3D fax of a happy buddha (by Brian Curless)	Logo of the Digital Michelangelo Project	Fragment from the giant marble puzzle of the Forma Urbis Romae Project	Light Field Rendering, my most- cited paper (with Pat Hanrahan)	Stanford multi-camera array, and relatives	Light Field Microscope Project

	I love teaching. After becoming full-time at Google, and finding people there who wanted to know more about photography, I decided to teach a revised but nearly full version of my Stanford course CS 178 (Digital Photography) at Google. These lectures were recorded and edited to remove proprietary material, at which point Google permitted me to make them public. Here is a link to this course, which I called Lectures on Digital Photography. I also uploaded the lecture videos as a YouTube playlist, where to my surprise they went viral in September 2016. A Googler made a word cloud (at left) algorithmically from the comments on those videos and sent it to me as a gift. In a word cloud the size of each word is proportional to the number of times it appears in the text being processed by the algorithm. It's one of the nicest gifts I have ever received.
	For several years my research focused on making cameras programmable. One concrete outcome of this project was our Frankencamera architecture, published in this SIGGRAPH 2010 paper and commercialized in Android's Camera2/HAL3 APIs. To help me understand the challenges of building photographic applications for a mobile platform, I tried writing an iPhone app myself. The result was SynthCam. By capturing, tracking, aligning, and blending a sequence of video frames, the app made the near-pinhole aperture on an iPhone camera act like the large aperture of a single-lens-reflex (SLR) camera. This includes the SLR's shallow depth of field and resistance to noise in low light. The app launched in January 2011, and seeing it appear in the App Store was a thrill. I originally charged $0.99, but eventually made it free. Here are a few of my favorite reviews of the app: MIT Technology Review, WiReD, The Economist. Unfortunately, with my growing involvement at Google I stopped maintaining the app, and it stopped working with iOS 11. That said, SynthCam's ability to SeeInTheDark inspired the development of Night Sight, described in more detail below under My Google career.
	In 1999 the National Academies published Funding a Revolution: Government Support for Computing Research. This landmark study, sometimes called the Brooks-Sutherland report, argued that research in computer science often takes 15 years to pay off. The iconic illustration from that report is reproduced at right. In 1996 Pat Hanrahan and I begin working on light fields and synthetic focusing, supported by the National Science Foundation. In 2005 Ren Ng, a PhD student in our lab, worked out an optical design that allowed dense light fields to be captured using a handheld camera. This design enabled everyday photographs to be refocused after they are captured. I worked on this technology alongside Ren in the Stanford Graphics Laboratory, and later applied it to microscopy, but the key ideas behind the light field camera were his. (Ren's doctoral dissertation, titled Digital Light Field Photography, received the 2006 ACM Doctoral Dissertation Award.) In the same year Ren started a company called Refocus Imaging to commercialize this technology. In 2011 that company, renamed Lytro, announced its first camera. So 15 years from initial idea to first product. An exciting ride, but a long wait. At left is the Lytro 1 camera, and below it the first picture I took using the camera, refocused after capture at a near distance, then a far distance. Unfortunately, aside from being refocusable Lytro cameras didn't take great pictures, and refocusability wasn't a strong enough differenting feature to drive consumer demand, so the product (and the follow-on Lytro Illum camera) weren't successful. Eventually, portrait modes on mobile cameras provided similar refocusing and shallow depth of field, but without sacrificing spatial resolution as microlens-based light field cameras do. While the synthetically defocused pictures produced by mobile cameras are not physically correct, it's hard to tell the difference. BTW, Ren Ng is now a professor in EECS at UC Berkeley.
	What do the two images at left have in common? In the mid-1990s, three students in my lab (Andrew Beers, Brian Freyburger, and Apostolos Lerios) left the PhD program to co-found Invisalign. The company's genesis is described in this Interesting Engineering article, from which the upper image at left was taken. Initially they planned to use 3D laser scanning (3rd image from left above). They later pivoted to taking a mold of your teeth, slicing the mold finely using a milling machine, and photographing each slice to build a 3D model. (They may have since pivoted to another technology.) This gave me an idea - why not slice everyday objects thinly, photograph each slice, and volume render the resulting stack of images? As an experiment, I glued together blocks of wood (lower image at left), sliced the block thinly using Invisalign's milling machine, and photographed each slice. Here's a grayscale video of the resulting image stack. The objects at lower right are pine cones embedded in resin. Isn't it interesting how wood grain changes shape over depth? Watch the knots move around in this block of maple. Knots are twigs from an early stage of tree growth, which eventually become embedded in the thickening branch from which they sprang. My plan was to volume render this and other natural objects (marble veining?), and write a book (or create a web site) of visualizations. I would call the book Volumegraphica (or Volumegraphia, inspired by Robert Hooke's 1665 book Micrographia, which contains beautiful drawings of what he could see through a microscope). An early attempt at volume rendering that block of maple is shown at right. Click on it for a video; you can clearly see the twig buried inside the block. Unfortunately, I never found time to puruse this sabbatical-type project, becoming involved instead in multi-camera arrays and light field microscopy (see images above). I also found it challenging to fix natural objects so they don't fall apart in the milling machine, especially if they contain cavities (like conch shells). For more details, see this slide deck. And for some related projects that use 3D medical imaging technologies instead of physical slicing, see the Visible Human Project, or this stunning volume rendering of a mouse tail from Resolution Sciences.

Note: I retired from Stanford in 2015. As the note in the box at the top of this page says, I am not accepting new PhD students, postdocs, visiting scholars, or summer interns.
Please don't email me asking about opportunities in my research group at Stanford; there is no such group, and there hasn't been one since 2015. Ask me instead about Adobe!

My Google career

Gaurav Garg taking video for CityBlock, later productized as Google StreetView	Figure 1 from US patent 7,586,655 on the design of a book scanner	Wearing Glass at a public photo walk, photo by Chris Chabot (2012)	Portrait Mode on Pixel 2, photo by Marc Levoy (2017)	Night Sight on Pixel 3, photo by Diego Perez (2018)	Astrophotography on Pixel 4 Florian Kainz (2019)	My portion of the Keynote address at the launch of Pixel 4 (2019)

In 1993, while as Assistant Professor at Stanford, I lent a few disk drives to PhD students David Filo and Jerry Yang so they could build a table of contents of the internet. This later became Yahoo. In 1996 Larry Page and Sergey Brin, also PhD students at Stanford, began assembling a pile of disk drives two doors down from my office to build an index of the internet. This later became Google. Hmmm, table of contents versus index... At the time both ideas made some sense, but history shows which approach scaled better as the internet grew. (While Larry shared an office with my grad students, I also got to know Sergey well, as a student in one of my computer graphics courses.)

In 2002 I launched a Google-funded Stanford research project called CityBlock, which Google later commercialized as StreetView. For an overview of the Stanford project, see this talk I gave at the 2004 Stanford Computer Science Department retreat. This article in TechCrunch outlines the project's later history at Google, except that the video Larry Page and Marissa Meyer captured while driving around San Francisco predated my project at Stanford, not the other way around as the article says. (I still have his video in my attic.)

In 2003, working as a consultant for Google, I co-designed the book scanner for Google's Project Ocean, whose goal was to non-destructively digitize millions of books from six of the world's largest libraries: the University of Michigan, Harvard (Harvard University Library), Stanford (Green Library), Oxford (Bodleian Library), and the New York Public Library. While the scanner design actually used in the project is a Google trade secret, the patent linked above is representative of the technologies we were exploring. See also this CNET article, or this coverage from National Public Radio. (Francois-Marie Lefevere, the co-inventor on this second patent, was formerly one of my students.)

From 2011 through 2020 I built and led a team at Google that worked broadly on cameras and photography, serving first as visiting faculty in GoogleX, and later as a full-time Principal Engineer and Distinguished Engineer in Google Research. The internal team name was "Gcam", which became public when this GoogleX blog article appeared. Our first project was burst-mode photography for high dynamic range (HDR) imaging, which we launched in the Explorer edition of Google Glass. See also this public talk. This work was later extended and applied to mobile photography, launching as HDR+ mode in the Google Camera app on multiple generations of Nexus and Pixel smartphones. The French agency DxO gave the 2016 Pixel the highest rating ever given to a smartphone camera, and an even higher rating to the Pixel 2 in 2017. Here are some albums of photos I shot with the Pixel XL: Desolation Wilderness, Cologne and Paris, New York City, Fort Ross and Sonoma County. Press "i" ("Info") for per-picture captions.

In 2017 we branched out from HDR imaging to synthetic shallow depth of field, based loosely on my 2011 SynthCam app for iPhones. The first version of this technology launched as Portrait Mode on Pixel 2 (see example above). Here is an album of portrait mode shots of people, and another of small objects like flowers. See also this interview in The Verge, this cute explanatory video about the Pixel 2's camera, and these papers in SIGGRAPH Asia 2016 on HDR+ and SIGGRAPH 2018 on portrait mode. We later extended portrait mode to use machine learning to estimate depth (published in ICCV 2019), and on Pixel 4 to use both dual-pixels and dual-cameras.

In 2018 my team developed (or collaborated with other teams on) several additional technologies: Super Res Zoom (paper in SIGGRAPH 2019), synthetic fill-flash, learning-based white balancing (papers in CVPR 2015 and CVPR 2017), and Night Sight (paper in SIGGRAPH 2019). These technologies launched on Pixel 3. Night Sight was inspired by my prototype SeeInTheDark app, which is described in this public talk, but was never released as a public app. Night Sight has won numerous awards, including DP Review's 2018 Innovation of the Year and the Disruptive Device Innovation Award at Mobile World Congress 2019. See also these inteviews by DP Review and CNET, and this lay person's video tutorial by the Washington Posts's Geoffrey Fowler.

In 2019 we launched a real-time version of HDR+ called "Live HDR+", which made Pixel 4's viewfinder WYSIWYG (What You See Is What You Get), and "Dual Exposure Controls", which allowed separate control over image brightness and tone mapping interactively at time of capture - a first for any camera. In Pixel 4 we also extended Night Sight to astrophotography. My team had been exploring this problem for a while; see this 2017 article by Google team member Florian Kainz. However, Florian's experiments required a custom-written camera app and manual post-processing. On Pixel 4 consumers could capture similar pictures with a single button press, either handheld or stabilized, such as Florian's stunning tripod photograph (see above) of the Milky Way over Haleakala in Hawaii. Note that pictures like this still require aligning and merging a burst of frames, because over a 4-minute capture the stars do move. Is there art as well as science in our work on Pixel phones? Lots of it; check out this short video by Google on how Italian art influenced the look of Pixel's photography.

Finally, my team also worked on underlying technologies for Project Jump, a light field camera that captures stereo panoramic videos for VR headsets such as Google Cardboard. See also this May 2015 presentation at Google I/O. A side project I did at Google in 2016 was to record a modified version of my quarter-long Stanford course CS 178 (Digital Photography) in front of a live audience (of Googlers). The videos and PDFs of these lectures are available to the public for free here. See also this YouTube playlist.

As an epilogue to this chronology, the technologies my team launched in Pixel phones from 2014 to 2019 were quickly adopted by other smartphone vendors. It seems fair to say that my team's work, and our publications, accelerated the use of smartphones for everyday photography, and disrupted the camera industry. (See also my sidebar below about cell phones versus SLRs.) I believe it was partly for this reason that I was inducted into the National Academy of Engineering in 2022. However, it's important to note that these technologies were developed by scrappy subteams of smart and creative people (led by Sam Hasinoff and Yael Pritch), not by me acting as some kind of "hero inventor". Our impact was also facilitated by Google executives (starting with Dave Burke) who believed in the team and were willing to risk their flagship product on our strange ideas.

Oh yes, and then there is the story about how Google got its name, due to a spelling mistake made by one of my Stanford graduate students.
To hear the full story, you'll have to treat me to a glass of wine.

  Will cell phones replace SLRs?

Although I've largely moved from SLRs to mirrorless cameras for my big-camera needs, I'm frankly using big cameras less and less, because they have poor dynamic range unless I use bracketing and post-processing, and they take poor pictures at night unless I use a tripod. Both of these use cases have become easy and reliable on cell phones, due mainly to computational photography. HDR+ mode on Nexus and Pixel smartphones is one example. These pictures were taken with the 2015-era Nexus 6P: the left image with HDR+ mode off, and the right image with HDR+ mode on. Click on the thumbnails to see them at full resolution. Look how much cleaner, brighter, and sharper the HDR+ image is. Also, the stained-glass window at the end of the nave is not over-exposed, and there is more detail in the side arches.

Taking a step back, the tech press is fond of saying that computational photography on cell phones is making big cameras obsolete. Let's think this through. It is true that sales of interchangeable-lens cameras (ILCs), which include SLRs and mirrorless cameras, have dropped by two-thirds since 2013, and point-and-shoot cameras have largely disappeared, in lockstep with the growth of mobile phones. Similarly, Photokina, the world's largest photography trade show, shrank by half from 2015 to 2020, and was finally canceled forever in 2021, having been partly supplanted by Mobile World Congress. There are confounding factors at play here, including the decimation of professional photography niches like photojournalism, due to shifts in how news is gathered and disseminated. But improvements in the quality of mobile photography over the last decade is certainly a contributor to these changes. Rishi Sanyal, Science Editor for DP Review, who has written extensively about Pixel 3 and Pixel 4, once estimated that the signal-to-noise ratio (SNR) of merged-RAW files from Pixel 4 matches that of RAW files from a micro-four-thirds camera. I think Pixel's dynamic range is actually better - roughly matching that of a full-frame camera, due to low read noise on Sony's recent mobile sensors, but in either case the trend is clear. I also note that as we move from SLRs to mirrorless cameras, hence from optical to electronic viewfinders, the dynamic range of the viewfinder becomes more important. In this respect the Pixel 4, with its "Live HDR+", firmly beats the electronic viewfinders on big mirrorless cameras. (The SNR of cell phone viewfinders still lags, but I expect this to become better in the future.) When Pixel 2 won DP Review's Innovation of the Year in 2017, comments in the user forums were running 60/40 in favor of "This isn't real photography." By the time Pixel 3 won the same award again in 2018, user forum comments were running 80/20 in favor of "Why aren't the SLR makers doing this?" Actually, a few mirrorless cameras do offer single-shutter-press burst capture and automatic merging of frames. But as of 2020 these modes produce only JPEGs, not merged RAW files, and their merging algorithms use only global homographies, not robust tile-by-tile alignment. As a result they work poorly when the camera is handheld or there is motion in the scene.

It's hard to resist concluding that this is a classic case of "disruptive technology", as described by Clayton Christensen in The Innovator's Dilemma. Cell phones entered at the bottom of the market, so traditional camera makers didn't see them as a threat to their business. Slowly but inexorably, mobile photography improved, due to better sensors and optics, and to algorithmic innovations by Google and its competitors. Computational photography played a role, and so did machine learning. So also did Google's culture of publication, which allowed other companies to become "fast-followers". By the time traditional camera companies realized that their market was in danger it was too late. Even now (in 2020), they seem slow to respond. I analyzed their slowness in this 2010 article, the same year we published our Frankencamera architecture (commercialized by Google in its Camera2/HAL3 API). Little has changed since then, except that cell phones have become more capable. Full disclosure: one factor I missed in my 2010 article was that while large cameras have powerful special-purpose image processing engines, they have relatively weak programmable processors. At the same time, they have more pixels to process than cell phones, because their sensors are larger. These two factors made innovation difficult.

In the end, it's hard to avoid thinking it's "Game Over" for ILCs, except in niches like sports and wildlife photography, where big glass is mandated by the laws of physics. Even Annie Leibovitz thinks this. For the rest of us, it's not only that "the best camera is the one that's with you"; it may also be true that the camera that's with you (meaning your cell phone) is your best camera!

ChatGPT's version of this sidebar, rewritten in hip-hop style.

My Adobe career

A history yet to be written. 😉

But we're hiring! Especially MS and PhD graduates with expertise in computational photography, computer vision, and machine learning.
Meanwhile, see this 1-hour, in-depth podcast / interview by Nilay Patel of The Verge, on camera hardware, software, and artistic expression at Google and Adobe.
And this 10-minute talk at Adobe MAX 2020 about computational photography at the point of capture.
In March 2022 Adobe interviewed me about my work in photography, following my election to the National Academy of Engineering. See also this coverage in Petapixel.
Here's a nice July 2022 interview by Atila Iamarino of Brazilian public television, about computational photography in general, presented in a mix of English and Portuguese.
Here is my Adobe team's gift to me of a superhero backstory.

Here is an Adobe Max 2023 Sneak Peek that my team presented on automatically removing undesirable window reflections. The first image at left is a smartphone photo I captured of a phonograph turntable in a Zurich storefront. Our AI produces the second image, with the reflections (mostly) removed, and optionally the third image, showing the reflected scene. In this image you can see me standing in front of the store with my umbrella, because it was raining. Features in this image appear doubled (or more) due to presence of double-pane glass. The Sneak was called #projectseethrough. Here is a video of the live presentation in Los Angeles by team member Eric Kee. Twitter/X seemed to like the presentation.

Also featured at Adobe MAX 2023 were versions of Lightroom and Adobe Camera Raw (ACR) that support editing of high dynamic range (HDR) images. Adobe collectively calls these capabilities HDR Optimization. For more details on this technology, see this blog by ACR architect Eric Chan. If you stopped by the Lightroom booth at MAX, you might have seen the photograph at left that I took in the dining room of Yosemite's Ahwanhee Hotel. The first image is standard dynamic range (SDR), and the second is high dynamic range (HDR). To see the second one, you must be viewing this web page in Chrome version 117 or later on a suitable HDR display, such as a 14" or 16" Macbook Pro 2021 or later, or an Apple XDR monitor. The third image includes some guy having his morning coffee, with help from Photoshop Generative Fill. For more examples of SDR/HDR pairs, see this album from a recent trip to France and Switzerland.

Launched at MAX 2024 was a new feature of Adobe Camera Raw (ACR) called the Adobe Adaptive Profile. Assigning a profile to a photo determines how the photo is rendered in the absence of manual adjustments. Unlike existing ACR profiles, Adobe Adaptive is image dependent and semantically aware (e.g. subjects and skies). It is implemented using an AI trained on thousands of hand-edited photos. (I was one of the editors.) The first image at left is a raw HDR photograph. (View using Chrome on a suitable HDR display.) The people are too dark, and the sky and surf are distractingly bright. The second image shows the effect of our AI. The people have been brightened, and the sky has been darkened. Our AI applies brightness manipulations using a grid of tone curves called a Profile Gain Table Map (PGTM), and color manipulations using a set of three-dimensional RGB lookup tables (RGBTs). The third image illustrates the PGTM. Below this image is a band of color. The image tells you whether pixels of the photograph that have the brightness shown in the band will be darkened or brightened by our AI. As you can see, the PGTM calls for the couple's clothing, which are initially dark, to be brightened by 1 f-stop. If the band were nearly white, it would show that the PGTM calls for the sky to be darkened by 1.5 f-stops. For more details, see our Adobe blog.

Photography

Turkey, June 2015	Myanmar, December 2016	Antarctica, December 2017	Italy, Switzerland, Germany, 2018	Barcelona, February 2019	New York, March 2020

(Mostly) nature shots	New York, January 2020	Pixel 4 launch event	Prague to Vienna by bicycle	Eastern Sierras, August 2019	Portrait Blur on famous paintings

India, December 2008	Thailand/Cambodia, December 2013	Chile and Patagonia, December 2015	Van trip across EU, June 2016	Croatia and Italy, June 2017	Tour of the Baltics, June 2018

Autobiography

	In 2012 I was invited to give the commencement address at the 2012 Doctoral Hooding Ceremony of the University of North Carolina (from which I graduated with a doctorate in 1989). After the ceremony a number of people asked for the text of my address. Here it is, retrospectively titled "Where do disruptive ideas come from?". Or here is UNC's version, with more photos like the one at left. And here is the video.
	Portrait photographer Louis Fabian Bachrach took some nice photographs (here and here) of me in 1997 for the Computer Museum in Boston (now closed). I do occasionally wear something besides blue dress shirts. Here are shots with other shirts, from August 2001 and July 2003. Yes, that's a Death Ride T-shirt in the last shot. I also rode in 2005, and yes, I finished all 5 passes - 15,000 feet of climbing. That's why I'm smiling in the official ride photograph (shown at left), taken at the top of Carson Pass after 12 hours of cycling.
	During a 1998-99 sabbatical in Italy, my students and I digitized 10 of Michelangelo's statues in Florence. We called this the Digital Michelangelo Project. Here are some photographic essays about personal aspects of the sabbatical. In particular, I spent the year learning to carve in marble. At left is my first piece - a mortar with decorated supports. Here are some sculptures by my mother, who unlike me had real talent.
	The Digital Michelangelo Project was not my first foray into measuring and rendering 3D objects. Here are some drawings I made in college for the Historic American Buildings Survey. In this project the measuring was done by hand - using rulers, architect's combs, and similar devices.
	I still like finding and measuring old objects, especially if it involves getting dirty. This photographic essay describes a week I spent on an archaeological dig in the Roman Forum. The image at left, taken during the dig, graces the front cover of The Bluffer's Guide to Archaeology.
	My favorite radio interview, by Noah Adams of National Public Radio's All Things Considered - about the diverging gaze directions of the two eyes in Michelangelo's David (June 13, 2000). (Click to hear the interview using RealAudio at 14.4Kbs or 28.8Kbs, or as a .wav file.)
	This interview, by Guy Raz, weekend host of All Things Considered, runs a close second. It's about the Frankencamera (October 11, 2009), pictured at left. (Click here for NPR's web page containing the story and pictures, and here for a direct link to the audio as an .mp3 file.) Finally, here's a text-only interview at SIGGRAPH 2003, by Wendy Ju, with reminiscences of my early mentors in computer graphics.
	Speaking of computer graphics, I'm fond of the front cover of the Siggraph 2001 proceedings. The image is from a paper (in the proceedings) on subsurface scattering, co-authored with Henrik Wann Jensen, Steve Marschner, and Pat Hanrahan. And check out this milk. This paper won a Technical Academy Award in 2004. Subsurface scattering is now ubiquitous in CG-intensive movies.
	However, not everything went smoothly at Siggraph 2001. A more-strenuous-than-expected after-Siggraph hike inspired Pat Hanrahan's and my students to create this humorous movie poster. Click here for the innocent version of this story. And here for the real story.

Genealogy

	A lot of my early Stanford research related to volume data. The cause may be genetic. My mother's cousin David Chesler is credited with the first demonstration of filtered backprojection, the dominant method used in computed tomography (CT) and positron emission tomography (PET) for combining multiple projections to yield 3D medical data. Here is a description of his contributions.
	My father's genes also seem to be guiding my research tastes. Optics has been in my family for four generations. My father Barton Monroe Levoy and my grandfather Monroe Benjamin Levoy were opticians and sellers of eyeglasses through their company, Tura. At left is an early brochure. Tura is still alive and well, with corporate headquarters in New York City, although it is no longer in the family. Here is a marvelously illustrated timeline they assembled about the history of the company; it includes the image at left.
	Going back further, my great-grandfather Benjamin Monroe Levoy sold eyeglasses, cameras, microscopes, and other optical instruments in New York City a century ago. Here is a piece of stationery from his store. He later moved to 42nd street, as evidenced by the address on the case of these eyeglasses, remade as pince-nez with a retractor. (At left is a closeup of the embossed address.) And here is a wooden box he used to mail eyeglasses to customers. The stamp is dated 1902.
	In the drawing (at left) illustrating that stationary, I believe you can see a microscope. In any case I have an old microscope from his store. This specimen of a silkworm mouth, which accompanied the microscope, appears in our SIGGRAPH 2006 paper on light field microscopy.
	My great-grandfather apparently also sold binoculars from the store. This pair, made by Jena Glass about 80 years ago and inscribed with the name B.M. Levoy, New York, was recovered by a SWAT team during a drug raid in South Florida in 2008. They have undoubtedly passed through many hands during their long and storied life. It would be fascinating to watch a video of everything these lenses have seen.
	When my Stanford students worked with me at the optical bench, they were perplexed by my arcane knowledge of mirror technology. Returning to my mother's side of the family, my great-grandfather Jacob Chesler built a factory in Brooklyn (pictured at left) that made hardware. The building passed to my grandfather Nathan Chesler, who converted it to making decoratively bevelled mirrors. I spent many pleasant hours studying the factory's machinery, designed by my uncle Bertram Chesler, for silvering large plate-glass mirrors.