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9 Amazing Portraits That Changed Art

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Anyone can snap a selfie. These passionate artists created portraits that changed art forever.

1. “Portrait of Wally” by Egon Schiele

The painting of Schiele’s mistress is called the “face that launched a thousand lawsuits” for a reason. After being lost during World War II, Wally remained missing until 1997, when she somehow ended up in an American museum—an appearance that angered the Austrian government, which claimed ownership. It sparked a 13-year court battle that has influenced every art restitution case since.

2. “Portrait of Gustave Geffroy” by Paul Cezanne

Having your portrait painted by Cezanne was like running a marathon. The artist studied his subjects so intensely that he could not paint them in one fell swoop, but sometimes needed them to pose over 100 times. (For Geffroy’s portrait, Cezanne took three months.) The hard angles in Geffroy’s portrait inspired Cubists years later. 

3. “Portrait of Madame X” by John Singer Sargent

Everyone was shocked when Madame X was unveiled. Although nude paintings were everywhere, this painting was considered by far the most sexual many viewers had seen. Having posed as the model, Virgine Gautreau found her reputation briefly dashed, losing her status as Paris’s prime arm candy. Now lauded for being both revealing and concealing, the portrait is considered one of the greatest ever made.

4. All of Mary Cassatt’s portraits

Mary Cassatt may have grown up in Pittsburgh, but her portraits look like they came straight from France. Capturing the subtle social and private lives of women, Cassatt was one of the first women to successfully make painting her full-time job. By the looks of it, she was just as talented—if not more talented—as the men.

5. “The Blue Boy” by Thomas Gainsborough

Back in the 18th century, lots of portraits looked like colorless voids—a palette of drab browns and grays. Artist Joshua Reynolds even dictated, “Masses of light in a picture be always of a warm, mellow colour, yellow, red, or a yellowish white, and that the blue, the grey, or the green colours be kept almost entirely out of these masses.” Thomas Gainsborough called that hogwash. He defied convention and sparked a surge in color with this brightly lit portrait of a boy in blue.

6. “Whistler’s Mother” by James McNeill Whistler

Painted in 1871, some call this portrait the “Victorian Mona Lisa.” Although Whistler didn’t consider it a portrait—he felt it was a study in black and gray—it’s since become an icon for motherhood. Few paintings have been copied more.

7. “Pope Innocent X” by Diego Velazquez

The granddaddy of them all, art historians all over call this the greatest portrait of all time. The subject’s ruddy complexion is incredibly precise, arguably making it the most realistic portrait ever made. (When the pope first saw it, he recoiled and called it “too real.”) Velazquez did something that few people in the 17th century could do—he made one of the world’s most powerful men look human.

8. All of Van Gogh’s Self Portraits

In his final years, Van Gogh painted over 30 self-portraits. More than beautiful paintings, those portraits are records of every alteration of the artist’s technique—and a portal into how he viewed himself during those whirlwind years. Painted in 1889, his last portrait commanded one of the highest prices for a painting of all time, going for $71 million.

9. “Adele Bloch-Bauer I” by Gustav Klimt

Sold for $135 million in 2006, Klimt’s golden masterwork is one of the most expensive paintings ever sold. The portrait’s complex ornamentation helped establish the Art Nouveau movement, a style that has heavily influenced modern architecture, sculpture, and—of course—painting. 

Want to see your passions and connections to your friends? Check out Nissan's Passion Genome to create your interactive Passion Portrait and share the passions that make you, you.

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Name the Author Based on the Character
May 23, 2017
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