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Source: This article was published windowscentral.com By DAN THORP-LANCASTER - Contributed by Member: Olivia Russell

Microsoft's visual search is graduating from beta, now rolling out for everyone on iOS.

following a short period of beta testingMicrosoft Edge is now rolling out an intelligent visual search for everyone. The addition brings the iOS version of the app up to par with its Android counterpart, which picked up a visual search in June. But beyond that, there are a few other neat features tagging along in this update as well, including paste-and-search and the option to choose from more default search engines.

As for the highlight feature of this update, visual search lets you quickly snap a photo or choose one from your camera roll, then search the internet for information based on whatever you snapped. Microsoft is talking up the feature's usefulness for shopping, helping to track down items of clothing, for example, that you like. That's also bolstered by a built-in barcode scanner, which can be used to find deals on items. Visual search can be used to find more information on landmarks around you as well.

Here's a full look at all of what's new in this update:

  • Intelligent visual search gives you a cool new way to find contact info, identify landmarks, or find similar images based on a photo
  • Support paste and go/search in address bar
  • Choose from more default search engine options
  • Performance improvements

And if you're signed in with a work or school account, there are a few other goodies to check out:

  • See your organization's home page
  • Securely access intranet sites from home
  • See mobile browser activity on your PC's timeline

If you're giving Microsoft Edge a shot on your iPhone or iPad, you can check out all of these new features by grabbing the latest update from the App Store now.

Categorized in Search Engine

Pinterest said today it’s launching three new products today that will point out specific elements in pictures — whether viewed live through a camera or through a typical image search — and use them as a jumping point for search.

All of these are designed to keep Pinterest coming back over and over to discover ideas based on images. Pinterest has been increasingly trying to close the gap from a user initially viewing an image to being able to jump to ideas and products with a single step, and adding these new in-image search capabilities is another step toward that.

“Early information technology used words to connect ideas, like hyperlinks,” co-founder and chief product officer Evan Sharp said. “Search engines we built today have drafted on that, they rely on words to get you answers to your questions. But when it comes to searching for ideas, words aren’t the right way. Sometimes you don’t really know what you’re looking for until you see it.”

So let’s break down each product, starting with the most important one, Lens. That gives users a way to open their camera, look at any image and Pinterest’s Lens feature will automatically pick apart the objects in an image. That can drill down into foods, animals, or even patterns like hexagons. That gives users the ability to start searching for related elements through that. Lens is launching in beta today on iOS.

pinterest lens results

The main reason why this is so critical is that it means Pinterest may be able to capture that brief moment that a customer might have to just make an impulse purchase. That moment can be incredibly fleeting, and lowering the friction toward seeing something in the real world and making that purchase can capture that in a way that other companies may not be able.

Pinterest is also updating its visual search when it comes to finding specific products, isolating each product within an image. So if you’re looking at a pin from a company that may be selling a jacket, it will also pick up the image of the boots and let you jump to them. Users can also jump to additional related content to those products or elements in the photo. With most of Pinterest’s content coming from Pinterest, this gives Pinterest a way to seamlessly jump through products — and offers businesses a way to build awareness for their other products.

pinterest shop the look

Instant Ideas adds a small little circle to the bottom of each pin, allowing them to jump straight into related elements and gather additional ideas related to that topic. This one seems pointed toward getting users to find products and ideas that they’ll save on their Pinboards — like recipes or potential styles.

pinterest instant ideas

Pinterest has largely become synonymous with visual search, which has become the company’s specialty and point of differentiation against other networks. With 150 million users, Pinterest is geared toward getting people to come in and start sort of wandering around to discover ideas and products they might not have known they wanted.

 

However, we’re starting to see some of these tools trickle down into other services, though maybe in a different fashion. Houzz, for example, breaks down specific products in a photo of a room or home that users can purchase. There are startups like Clarifai want to equip small businesses with similar visual search tools, though they take more of a metadata and tagging approach that can train their algorithms. And there’s always Google, which has invested heavily in visual search, but has yet to necessarily weaponize it in the same way Pinterest has for potential advertisers.

 

Nevertheless, these Pinterest products are a potential gold mine for those marketers. Pinterest is able to potentially engage with users at different points in their purchasing lifetime. Whether that’s in the mode where they are looking to discover ideas — and build brand awareness — to drilling them into finding a specific product and buying it, Pinterest offers a wide range of advertising products to get at each part of the customer’s shopping timeline.

Pinterest is going to have to solidify its pitch that it is one of the best visual search companies in order to continue to woo advertisers, which may still be treating Pinterest as more of a curiosity than a consistent ad buy. Pinterest is going to have to battle Snap, which is expected to go public next year, as a tool for building brand awareness and capture a potential customer’s attention at the beginning of their shopping lifetime. And there’s always Facebook, which has become a mainstay of marketers.

That’s going to come through a combination of new ad products — like its new addition of search ads — and also by improving its suite of products that it can present to advertisers as unique and differentiated from traditional ad buys. Pinterest, while growing quickly, was a bit off targets it initially set in early 2015 and has to figure out how to re-adjust its expectations as to what kind of advertising and consumer products marketers want.

 

“These three new products make anything in the world an entry point to the 100 billion ideas in Pinterest,” Pinterest CEO and co-foudner Ben Silbermann said. “Together they create a whole new discovery experience that’s unlike anything that’s out there today. You can get ideas whether you’re opening the app or walking through town. The more people the use it, the better the results become, the more we can recommend inspiring ideas.”

Author : Matthew Lynley

Source : https://techcrunch.com/2017/02/08/pinterest-adds-visual-search-for-elements-in-images-and-through-your-camera/

Categorized in Social

Visual search on the web has been around for some time

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In 2008, TinEye became the first image search engine to use image identification technology, and in 2010, the Google Goggles app allowed users to search the physical world with their phone cameras.

But in the last couple of years, visual search has come into new prominence, with companies like Pinterest and Bing developing into serious contenders in the visual search space, and search engines like Splash conceptualising new ways to search the web visually.

We now have an impressive range of visual search methods available to us: we can search with images, with part of an image, with our cameras, with paint on a digital canvas. And combined with applications in ecommerce, and recent advances in augmented reality, visual search is a powerful tool with huge potential.

So what can it do currently, and where might it develop in the future? 

Then and now: The evolution of visual search

Although the technology behind image search has come on in leaps and bounds in the past few years, it’s as a result of developments that have taken place over a much longer time period.

Image search on the web was around even before the launch of reverse image search engine TinEye in 2008. But TinEye claims that it was the first such search engine to use image identification technology rather than keywords, watermarks or metadata. In 2011, Google introduced its own version of the technology, which allowed users to perform reverse image searches on Google.

Both reverse image searches were able to identify famous landmarks, find other versions of the same image elsewhere on the web, and locate ‘visually similar’ images with similar composition of shapes and colour. Neither used facial recognition technology, and TinEye was (and still is) unable to recognise outlines of objects.

A screenshot of Google reverse image search in 2011. The search is for an image of some sandy yellow peaks and valleys with a blue backdrop. The results page says 'Best guess for this image: death valley national park zabriskie point'. The top two results are a Wikipedia page and a Tripadvisor page for Zabriskie Point, with a grid of visually similar images below.

 

Google reverse image search in 2011. Source: Search Engine Land

Meanwhile, Google Goggles allowed users of Android smartphones (and later in 2010, iPhones and iPads) to identify labels and landmarks in the physical world, as well as identifying product labels and barcodes that would allow users to search online for similar products. This was probably the first iteration of what seems to be a natural marriage between visual search and ecommerce, something I’ll explore a bit more later on.

The Google Goggles app is still around on Android, although the technology hasn’t advanced all that much in the last few years (tellingly, it was removed as a feature from Google Mobile for iOS due to being “of no clear use to too many people”), and it tends to pale in comparison to a more modern ‘object search’ app like CamFind.A mobile screenshot of a Google Goggles search. The screen shows a small bottle of Carex antibacterial hand gel with skin conditioners. A green square surrounds the product label, and a text string at the bottom of the screen reads: with skin DRYING tioners Carex

CamFind is a visual search and image recognition mobile app that was launched in 2013, and while it doesn’t appear to be able to solve Sudoku puzzles for you, it does have an impressive rate of accuracy.

Back when Google Glass was still a thing, Image Searcher, the startup behind CamFind, developed a version of the app to bring accurate visual search to Google Glass, activated by the command “OK Glass, what do you see?” This is the kind of futuristic application of visual search that many people imagined for a technology like Google Glass, and could have had great potential if Google Glass had caught on.

A mobile screenshot showing a successful CamFind object search. At the top is an image of a black keyboard. Below it is the word 'found'. Then reading downwards in a column are the words 'Black Lenovo corded keyboard'.

 The CamFind mobile app has an impressive accuracy rate, even down to identifying the brand of an object.

When the ‘pinboard’-style social network Pinterest launched in 2012, it was a bit of a dark horse, gaining huge popularity with a demographic of young-to-middle-aged women but remaining obscure in most conventional tech circles. Even those who recognised its potential as a social network probably wouldn’t have guessed that it would also shape up into a force to be reckoned with in visual search.

But for Pinterest, accurate visual search just makes sense, as it allows Pinterest to serve relevant Pin recommendations to users who might be looking for something visually similar (say, the perfect copper lamp to light their living room) or hone in on the specific part of a Pinned image that interests them.

In 2014, Pinterest acquired VisualGraph, a two-person startup which was cofounded by one of Google’s first computer vision engineers, bringing the company’s visual search know-how into the fold. In the same year, it introduced and began refining a function that allowed users to highlight a specific part of a Pin and find other Pins that are visually similar to the highlighted area – two years ahead of Bing, who only introduced that functionality to its mobile image search in July 2016.

Bing has pipped Pinterest to the post by introducing visual searching with a smartphone camera to its native iOS app (I can’t comment on how accurate it is, as the Bing iOS app is only available in the US), something that Pinterest is still working on launching. But it’s clear that the two companies are at the vanguard of visual search technology, and it’s worth paying attention to both to see what developments they announce next.

A gif showing Pinterest's visual search in action on a smartphone, detecting objects around a room and bringing up related pins at the bottom of the screen.

Meanwhile, Google is yet to offer any advance on Google Goggles for more accurate searching in the physical world, but you can bet that Google isn’t going to let Pinterest and Bing stay ahead of it for too long. In July, Google announced the acquisition of French startup Moodstocks, which specialises in machine learning-based image recognition technology for smartphones.

And at Google I/O in May, Google’s Engineering Director Erik Kay revealed some pretty impressive image recognition capabilities for Google’s new messaging app, Allo.

“Allo even offers smart replies when people send photos to you. This works because in addition to understanding text, Allo builds on Google’s computer vision capabilities to understand of the content and the context of images. In this case, Allo understood that the picture was of a dog, that it was a cute dog, and even the breed of the dog. In our internal testing, we found that Allo is 90% accurate in determining whether a dog deserves the ”cute dog” response.”

Visual search and ecommerce: A natural partnership

How many times have you been out and about and wished you could find out where that person bought their cool shoes, or their awesome bag, without the awkwardness of having to approach a stranger and ask?

What if you could just use your phone camera to secretly take a snap (though that’s still potentially quite awkward if you get caught, let’s be honest) and shop for visually similar search results online?

Ecommerce is a natural application for visual search, something which almost all companies behind visual search have realised, and made an integral part of their offering. CamFind, for example, will take you straight to shopping results for any object that you search, creating a seamless link between seeing an item and being able to buy it (or something like it) online.

A mobile screenshot from the app CamFind. At the top is a picture of a small bottle of Carex anti-bacterial hand gel, rotated 90 degrees to the left. Text at the top reads 'Carex Moisture Plus Hand Gel'. Below this are web results and related images for Carex Moisture Plus Hand Gel.

Pinterest’s advances in visual search also serve the ecommerce side of the platform, by helping users to isolate products that they might be interested in and smoothly browse similar items. An ‘object search’ function for its mobile app would also be designed to help people find items similar to ones they like in the physical world on Pinterest, with a view to buying them.

 

With the myriad possibilities that visual search holds for ecommerce, it’s no surprise that Amazon has also thrown its hat into the ring. In 2014, it integrated a shopping-by-camera functionality into its main iOS app (and has since released the function on Android), and also launched Firefly, a visual recognition and search app for the Amazon Fire Phone.

Even after the Fire Phone flopped, Amazon refused to give up on Firefly, and introduced the app to the more affordable Kindle Fire HD. The visual search function on its mobile app works best with books, DVDs and recognisably branded objects, but it otherwise has a good rate of accuracy.

A screenshot of Amazon's visual search for its mobile app in action. The main part of the screen shows the cover of a book, The Master Switch by Tim Wu. A collection of bright blue points clings to the title and author, and a tick icon shows that the app has successfully identified the book.

Amazon’s visual search in action.

Other companies operating in the cross-section of visual search and ecommerce which have emerged in the past few years include Slyce, whose slogan is “Give your customer’s camera a buy button”, and Catchoom, which creates image recognition and augmented reality tools for retail, publishing and other sectors.

Although searching the physical world has yet to cross over into the mainstream (most people I’ve talked to about it aren’t even aware that the technology exists), that could easily change as the technology becomes more accurate and increasingly widespread.

But ecommerce is only one possible application for visual search. What other uses and innovations could we see spring up around visual search in the future?

Source : searchenginewatch

Categorized in Internet Technology

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