Jelly Supplies Crowdsource-Powered Image Search

February 10, 2014

Here’s a new way to search from one of the minds that helped loose Twitter upon the world. The Los Angeles Times shares an interview with a Twitter co-founder in, “Biz Stone Answers our Questions About New Q&A App Jelly.” Forget algorithms; this app lets you take or upload a picture and pose a question about it to other humans, both within and outside your social-media circles.

Stone and co-founder, Ben Finkel, started with a question: if we were to design a search tool around today’s online landscape, as opposed to the one that existed about a decade ago, what would it look like? As the app’s website explains, “It’s not hard to imagine that the true promise of a connected society is people helping each other.” (Finkel, by the way, founded Q&A site Fluther.com and served as its CEO until that service was acquired by Twitter in 2010.)

One of Jelly‘s rules may annoy some: users cannot post a question without including an image. Writer Jessica Guynn asks Stone why he incorporated that requirement. He responds:

“We did a lot of testing and more often than not, an image very much deepens the context of a question. That’s why we made it so you can either take a picture with your camera and say, ‘What kind of tree is this?’ Or you can pull from the photo albums you already have. Or you can get [a photo] from the Web. Photos are what make mobile mobile. We are really taking advantage of the fact that this is a mobile native application…. Everyone is carrying around these great cameras. It’s a uniquely mobile experience to pair a short question with a photo. It might frustrate a few people in the long run but it will only end up with better quality for us. There is a higher bar to submitting a question.”

The image requirement is just one way Jelly differs from Twitter. The team also worked toward making the new app less conversational in order to avoid the clutter of non-answers. (And we thought 140 characters was limiting.) We’re curious to see how well users will warm to this unique service.

Cynthia Murrell, February 10, 2014

Sponsored by ArnoldIT.com, developer of Augmentext

Google: A New Way to Search and Sell Ads Too

July 20, 2012

LifeHacker catches us up with some developments in “Remains of the Day: Google Image Search Gets Knowledge Graph Integration.” The headlining item promises smarter and more comprehensive “Search by Image” results. The article quotes Google’s blog on a feature I’ve been looking forward to (the second one):

“Google updated its Image Search with a couple of new features. One being an expanded view that lets searchers see the text around matching images, and the other being added support for Knowledge Graph to image search results, which means Google will attempt to identity any photo that you upload or link to and provide more information about the subject.”

In other news, the write up notes that the Mac video player VLC is now at version 2.0.2, updated for Windows and OS X. Several small tweaks and bug fixes are addressed, and Retina Display support has been added. Also, Sparrow, an OS X email client, released an update to its desktop version. The update includes support for Retina Display and Mountain Lion. Amazon’s Flow app, already available for iOS, now brings barcode scanning and augmented reality to Android users.

Finally, Google is continuing its name-shuffle game. The Google Places iOS app follows the Google Places service in being renamed Google+ Local. A voice-search feature is now included in the app version.

Cynthia Murrell, July 20, 2012

Sponsored by PolySpot

CCFinder Offers Flexibility but How Far Do They Stretch

July 16, 2012

Creative commons offers a lot of versatility, but up until now the available finders have been limited. Flexibility was needed and AbelsSoft’s new creative commons image finder provides just that. Lifehacker’s article “CCFinder Simplifies Creative Commons Image Searches” talks about the pluses and minuses of this new program.

AbelsSoft offers a few perks when it comes to defining search, such as:

“You can filter your search to omit or include various types of CC restrictions such as non-commercial use only, references required to the original author, etc. Once you perform a search you can select a single or multiple images and either download to your preferred folder, visit the source image web site, or set the image as your desktop wallpaper.”

One taut aspect of CCFinder’s search engine is that it only utilizes Flickr, which ironically has the largest selection of CC licensed images available. Creative Commons offers users several sites to choose from, like Google Images, Open Clip Art Library, and Fotopedia, however users are still limited to one site per search.

The download is free for CCFinder, but registration does sign users up to receive an occasional newsletter. In itself, that is not a lot to ask for the convenience of well-defined search. AbelsSoft also offers a professional version of CCFinder that further defines how users search by implementing color filters. At first glance, CCFinder seems a user friendly program with search flexibility. We will have to see how far they stretch.

Jennifer Shockley, July 16, 2012

Sponsored by Polyspot

Short List of Image Search Tools

October 29, 2010

Short honk: One never knows when this type of list will be needed. “7 Image Search Tools That Will Change Your Life” provides descriptions, some screenshots, and links to seven image search tools. My life has not been changed, but a happy quack to Brain Pickings for the information. One example:

Retrievr at http://labs.systemone.at/retrievr/

Stephen E Arnold, October 29, 2010

Freebie

July Google Becoming Bing?

July 23, 2010

It seems that Google isn’t immune to adopting good ideas when it sees them in other places. Reading Google Positively Bing-Like With New Image Search Capabilities we see they’ve updated their search technology to view over 1000 images on each page. It shows that even Google knows when they need to change and keep moving ahead and it shows that they’re not immune to influences from the likes of Microsoft.

There are other noteworthy changes and these include increasing the density of the search results page and the ability to get a bigger preview of an image by hovering a mouse over it.

Of course no changes would be complete without some kind of advertising friendly features as well. Hence the new image format called Google Search Ads. Still the Microsoft influence makes us wonder whatever happened to innovation at Google? Strange for a company where searches are the lifeblood.

I don’t like the endless page “thing”. Latency remains an issue with certain network connections. How about a button to reclaim the “old” image search. Better yet, do something original.

Stephen E Arnold, July 23, 2010

Google Probes the Underbelly of AutoCAD

October 15, 2009

Remember those college engineering wizards who wanted to build real things? Auto fenders, toasters, and buildings in Dubai. Changes are the weapon of choice was a software product from Autodesk. Over the years, Autodesk added features and functions to its core product and branched out into other graphic areas. In the end, Autodesk was held captive by the gravitational pull of AutoCAD.

In one of my Google monographs, I wrote about Google’s SketchUp program. I recall several people telling me that SketchUp was unknown to them. These folks, I must point out, were real, live Google experts. SketchUp was a blip on a handful of users’ radar screen. I took another angle of view, and I saw that the Google coveted the engineering wizards when they were in primary school and had a method for keeping these individuals in the Google camp until they designed their last, low-cost fastener for a green skyscraper in Shanghai.

No one really believed that this was possible.

My suggestion is that some effort may be prudently applied to rethinking what the Google is doing with engineering software that makes pictures and performs other interesting Googley tricks. The first step could be reading the Introducing Google Building Maker article on the “official” Google Web log. I would gently suggest that the readers of this Web log buy a copy of the Google trilogy, consisting of my three monographs about Google technology. Either path will give you some food for thought.

For me, the most interesting comment in the Google blog post was:

Some of us here at Google spend almost all of our time thinking about one thing: How do we create a three-dimensional model of every built structure on Earth? How do we make sure it’s accurate, that it stays current and that it’s useful to everyone who might want to use it? One of the best ways to get a big project done — and done well — is to open it up to the world. As such, today we’re announcing the launch of Google Building Maker, a fun and simple (and crazy addictive, it turns out) tool for creating buildings for Google Earth.

The operative phrase is “every built structure on early”. How is that for scale?

What about Autodesk? My view is that the company is going to find itself in the same position that Microsoft and Yahoo now occupy with regard to Google. Catch up is impossible. Leap frogging is the solution. I don’t think the company can make this type of leap. Just my opinion.

Stephen Arnold, October 15, 2009
Another freebie. Not even a lousy Google mouse pad for my efforts.

Oracle Taps Brainware

October 15, 2009

The Reuters’s story “Brainware Signs OEM Agreement with Oracle for Intelligent Data Extraction” caught me and probably the folks at ZyLAB and other content processing companies by surprise. Brainware and its patented trigram technology has created strong believers in some markets such as litigation support. But the company has been working to strengthen its content acquisition functionality as well. The idea is that paper and electronic information enter at one end and searchable at the other. Oracle has been lagging in search. The Triple Hop technology has not taken center stage in my opinion. The Brainware deal seems to be for the content acquisition functions, what the news story calls “intelligent data capture”; that is, scanning and transforming functions plus entity extraction. Will Oracle embrace Brainware’s search and retrieval technology as well? Good question. Secure Enterprise Search needs some vitamins in my opinion. My hunch is that Oracle is beefing up its back end content intake system in order to deal with the increasingly successful Autonomy combine which continues to put pressure on big boys like Oracle. Brainware benefits from the publicity this tie up will produce. Search vendors, in my opinion, need this type of buzz to light up the radar of information technology professionals who too often focus on three or four search vendors, ignoring some interesting  alternatives.

Stephen Arnold, October 14, 2009

Microsoft Visual Search

October 7, 2009

The Inquirer has a knack for innovation. The story “Microsoft Demos Visual Search” provides a good description of a forthcoming Microsoft service. Images are grouped in galleries, making it easy to spot a particular image. The Inquirer reported, “Once a gallery has been selected, the images can be filtered and sorted through a series of sub-categories based on the gallery.” The Inquirer pointed out that the demo included 40 topics including dog breeds. Everything was flowing smoothly. The Inquirer then pointed out that the service would be particularly useful in an image segment popular with some folks but not discussed in polite circles. Kudos to Microsoft and to the Inquirer for its product application savvy.

Stephen Arnold, October 7, 2009

Google and Image Recognition

June 29, 2009

Not content with sophisticated image compression, Google continues to press forward in image recognition. Face recognition surfaced about a year ago. You can get some background about that home-grown technology in “Identifying Images Using Face Recognition”, US2008/0130960, filed in December 2006. The company has  long history of interest in non text objects. If you are not familiar with Larry Page’s invention “Method for Searching Media” US2004/0122811 was filed in 2003.

app of face recogniton

Source: Neven Technologies, 2006

The catalyst for the missing link between auto identified and processed images and assigning meaningful tags to images such as “animal” or “automobile” arrived via Google’s purchase of Neven Vision (originally I think the company used the “Eyematic” name. The switch seems to have taken place in 2003 or 2004.)

At that time, All Business described the company in this way:

Neven Vision purchased Eyematic’s assets in July 2003. Dr. Hartmut Neven, one of the world’s leading machine vision experts, led the technical team that created the original Eyematic system. Dr. Neven is also developing groundbreaking “next generation” face and object recognition technologies at USC’s Information Sciences Institute (ISI).

Google snagged with the acquisition the Eyematic patent documents. These make interesting reading, and I direct your attention to “Face Recognition from Video Images”, US6301370, which seems to be part of the Neven technology suite. The US patent document is – ah, somewhat disjointed.

Mixing Picasa, home grown technology, and the image recognition technology from Neven, Google had the ingredients for tackling a tough problem in content processing; namely, answering the question, “What’s that a picture of?”

Google provided some information in June 2009. A summary of Google’s image initiative appeared in Silicon.com, which published “Google Gets a New Vision When It Comes to Pictures”. (Silicon.com points to CNet.com which originally ran the story.) Tom Krazit reported:

Google thinks it has made a breakthrough in “computer vision”. Imagine stumbling upon a picture of a beautiful landscape filled with ancient ruins, one you didn’t recognize at first glance while searching for holiday destinations online. Google has developed a way to let a person provide Google with the URL for that image and search a database of more than 40 million geotagged photos to match that image to verified landmarks, giving you a destination for that next trip. The project is still very much in the research stage, said Jay Yagnik, Google’s head of computer vision research.

For me the key point in the Silicon.com story was that Google used its “big data” approach to making headway in image recognition. When matched to technology evolving from the FERET program, Google can disrupt a potentially lucrative sector for some big government integration firms.  The idea is that with lots of data, Google’s “smart software” can figure out what an image is about. Tapping Google’s clustering technology, Google’s Picasa image collection has been processed engineers to assign meaningful semantic tags to digital objects that don’t contain text.

Read more

Web Site Search: More Confusion

May 1, 2009

Diane Sterling, e-Commerce Times, wrote a story that appeared in my newsreader as a MacNewsWorld.com story called “The Wide Open World of Web Site Search”.

. You can find the article here. The write up profiles briefly several search systems; namely:

  • SLI systems here. I think of this company as providing a product that makes it easy to display items from a catalog, find indexed items, and buy a product. The company has added a number of features over the years to deliver facets, related searches, and suggestions. In my mind, the product shares some of the features of EasyAsk, Endeca, and Mercado (now owned by Omniture), among others.
  • PicoSearch here is a hosted service, and I think of it as a vendor offering indexing in a way that resembles Blossom.com’s service (used on this Beyond Search Web log) or the “old” hosted service provided by Fast Search & Transfer prior to its acquisition by Microsoft. Google offers this type of search as well. Google’s Site Search makes it easy to plop a Google search box on almost any site, but the system does not handle structured content in the manner of SLI Systems, for example.
  • LTU Technologies here. I first encountered LTU when it was demonstrating its image processing technology. The company has moved from its government and investigative focus to e-commerce. The company’s core competency, in my view, is image and video processing. The system can identify visual similarity. A customer looking at a red sweater will be given an opportunity to look at other jacket-type products. No human has to figure out the visual similarity.

Now the article is fine but I was baffled by the use of the phrase “Web site search”. The idea I think is to provide the user with a “finding experience” that goes beyond key word searching. On that count, SLI and LTU are good examples for e-commerce (online shopping). PicoSearch is an outlier because it offers a hosted text centric search solution.

Another issue is that the largest provider of site search is our good pal Googzilla. Google does not rate a mention, and I think that is a mistake. Not only does Google make it possible to search structured data but the company offers its Site Search service. More information about Site Search is here.

These types of round up articles, in my opinion, confuse those looking for search solutions. What’s the fix? I think the write up should have made the focus on e-commerce in the title of the article and probably early in the write up included the words “e-commerce search”. Second, I think the companies profiled should have been ones who deliver e-commerce search functions. None of the profiled companies have a big footprint in the site search world that I track. This does not mean that the companies don’t have beefy revenue or satisfied customers. I think that the selection is off by 15 degrees and a bit of a fruit salad, not a plate of carrots.

Why do I care?

There is considerable confusion about search. There are significant differences between a search system for a text centric site and a search system for a structured information site such as an e-commerce site. One could argue that Endeca is a leader in e-commerce. That’s fine but most people don’t know this side of Endeca. The omission is confusing. The result, in my experience, is that the reader is confused. The procurement team is confused. And competitors are confused. Search is tough enough without having the worlds of image, text, and structured data scrambled unnecessarily.

Stephen Arnold, May 1, 2009

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