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

Stephen E Arnold, October 29, 2010

Freebie

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

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.

Stephen Arnold, October 14, 2009

Stephen Arnold, October 7, 2009

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.

Google purchased Neven Vision in 2006, the same year it snagged Transformics, another pivotal Google purchase. Google said in 2006 in “A Better Way to Organize Photos”:

Neven Vision comes to Google with deep technology and expertise around automatically extracting information from a photo. It could be as simple as detecting whether or not a photo contains a person, or, one day, as complex as recognizing people, places, and objects. This technology just may make it a lot easier for you to organize and find the photos you care about. We don’t have any specific features to show off today, but we’re looking forward to having more to share with you soon.

The soon translated into a two or three year digestion and integration process. Face recognition became available in 2008. With the comment reported by Silicon.com and Cnet.com, Google will be dribbling out more image magic in the the months ahead. The go slow and surround and seep strategies are alive and well at Google in my opinion.

The key point is that Google continues to blend internal and acquired technology, then allowing Google engineers years to refine, adapt, and experiment. Based on my research, 2006 continues to be a hallmark year for Google technology. Acquisitions since 2006 have been interesting but continue to fill gaps, not provide leapfrog capabilities.

As Google deploys image recognition and other technology on its platform, I pay attention to the clumps of technology Lego blocks that Google possesses. For example, in law enforcement and intelligence, Google wizards can explore combinations of Postini (email), Neven (image recognition, mobile visual search), Keyhole (maps, gps), and other bits and pieces. With modest effort, Google could roll out an integrated law enforcement and intelligence system. Business Week nosed around this topic, but the publication left the story hanging. For example, a follow up with Neven technology hooked into a weapon systems suggests interesting lethal and sub lethal uses of the technology. Think about virtual surveillance zones. Think about processing images and video for face datasets using Gabor Wavelet ‘face template’ or a similar technology. Established players in this specialized niches may want to pay closer attention to the Google.

Stephen Arnold, June 29, 2009

. 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

So what are these two powerhouses doing?

According to Newsfactor here, the two companies are teaming up for digital asset reuse. Most organizations have an increasing amount of podcasts, videos, images, and other rich media. If you read my link tasty essay about content management (the mastodon) and the complexities of dealing with content objects in containers (tar pit), you know that there is an opportunity to go beyond search.

The Newsfactor story is called “Open Text, Endeca to Deliver Digital Asset Reuse”. My understanding of the Newsfactor version of the deal is that OpenText will integrate Endeca’s asset management system into OpenText content management systems. There are a number of product names in the write up, and I must confess I confuse them with one another. I am an old and addled goose.

What’s the implication of the tie up? I think that Autonomy’s push into asset management with its IDOL server and the Virage software has demonstrated that there’s money in those rich media objects that are proliferating like gerbils. The world of ediscovery has an asset twist as well. Videos and podcasts have to be located and analyzed either by software or a semi alert paralegal, maybe a junior lawyer. OpenText has a solid ediscovery practice, so there’s some opportunity there. In short, I think this tie up helps two established companies deal with a competitor who is aggressive and quicker to seize enterprise opportunities. Autonomy is a serious competitor.

What will Autonomy and other vendors do? I think that in this economic climate there will be several reactions to monitor. Some aggressiveness on the part of Autonomy and probably Adobe will be quick to come. Second, other vendors of search and content processing systems will shift their marketing messages. A number of search systems have this capability and some, like Exalead, can make videos searchable with markers where particular passages can be viewed in the video object. This is quite useful. You can see a demo here. Third, I think that eDiscovery companies already adept at handling complex matters and content objects will become more price competitive. Stratify comes to mind as one outfit that may use price as a counter to the OpenText and Endeca tie up. I can point to start ups, aging me-too outfits like IBM, and a fair number of little known specialists in rich media who may step up their marketing.

This will be interesting to watch. OpenText is a bit like the old Ling Temco Vought type of roll up. Endeca is a solid vendor of search and content processing technology that was unable to pull off an initial public offering and a recipient of cash infusions from Intel and SAP’s venture arm. The expectation is that one plus one will equal three. In today’s market, there’s a risk that a different outcome may result.

Stephen Arnold, April 17, 2009

A happy quack to the reader who pointed out that I did not mention that a videographer can make money by posting the content to Yidio. The procedure requires that the videographer provide his / her AdSense identification code. Click here for details.

Stephen Arnold, March 29, 2009

Stephen Arnold, January 13, 2009

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