Hyperlinking the Real World (Redux)

Thanks ReadWriteWeb for this redux on a great interactive-real-world phone app...

Written by Sarah Perez / April 5, 2009 6:00 PM / 8 Comments

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European researchers working on the MOBVIS project have developed a new system that will allow camera phone users to hyperlink the real world. After taking a picture of a streetscape in an urban area, the MOBVIS technology identifies objects like buildings, infrastructure, monuments, cars, and even logos and banners. It then renders relevant information on the screen using icons that deliver text-based details about the object when clicked.

This project goes beyond today's mapping applications like Google's Street View, for example, which first identifies your location either via GPS or triangulation and then shows you pictures of that area. Instead, MOBVIS actually lets you "see" the world through your mobile phone. This is computer vision, or rather, mobile vision.

Editor's note: During 2009 there have been some posts on ReadWriteWeb that didn't get the attention they perhaps deserved - because of timing, competing news stories, etc. So we're starting up our Redux series again, to re-publish some of those hidden gems. This is one of them, we hope you enjoy (re)reading it!

There are obviously numerous potential applications for such a technology. On the MOBVIS homepage, they offer up some scenarios for how their application could be used, including the following:

Tourism/Augmented City Maps: The MOBVIS technology could be used to inform visitors about the objects in an area be they buildings or landmarks. The images could also be annotated with additional information like history, event information, or information about nearby shops.

Visual Localization: For phones without GPS technology, triangulation could be combined with the computer vision technology to locate a user's position and orientation in a manner that would be comparable to GPS and just as accurate.

Motion Estimation: Also comparable to GPS, MOBVIS could enable continuous position updates to determine the location of objects in motion as well as their speed.

Incremental Map Updates: MOBVIS supports incremental updating of maps which would allow for the automated authoring of the urban infrastructure. No longer would Google need to send their vans around taking pictures of streets - the data could be uploaded from users' phones as they took their photos.

Picture-Driven Search Engine: Because the mobile phone could now "see" the surrounding landscape, the world - reality - becomes the backdrop for a sort of picture-driven search engine in which the objects in the world are all hyperlinked and annotated like a real-life semantic web.

How It Works

The MOBVIS system begins with a pre-populated database of geo-referenced panoramas (such as Google's Street View, perhaps). The objects in the images are then manually annotated with information. Once that's complete, the system is ready for search queries from mobile users. After a user takes a picture, MOBVIS compares the photo to the photos in its database and returns the relevant links.

The challenge here is getting a mobile phone picture to match up with the more pristine photos found in the database. The database photos would likely be clear, crisp, and detailed, but a user's photo could be grainy, taken on a dark and cloudy day, or taken from an odd angle.

The MOBVIS system's main strength comes from its feature-matching algorithm developed by the University of Ljubljana in Slovenia, one of the partners of the project. This algorithm can very accurately detect minute differences between similar objects. In real-world tests, it's reported that this system was highly accurate, detecting the right building 80 percent of the time.

Aleš Leonardis, head of the Ljubljana team, believes that number can be improved. He also notes that that the system, though not always right, was never wrong. "It was remarkable that there were no false positives," he says. "Sometimes the system couldn't identify a building, but it never put the incorrect link on a building."

You can read more about the research here on the MOBVIS project's homepage.

Axe does a Skittles

http://www.theaxeeffect.com/

Interesting to see companies creating their own 'webs on the web', rather than a a series of more or less independant sites and microsites. Having a series of branded and unbranded social media presences, linked to from a central hub and ideally plugged into freiend freed, tumblr and a load of other streaming platforms really does seem like a smarter way to get your brand online. I have to say i prefer Axe's approach to that of Skittles (http://www.skittles.com) as it gives that brand and how it like to portray content much more of a role (and a much more of a bill i imagine), rather than just tapping into content and keywords on existing sites.

Thoughts?

Bazaarvoice CEO stresses the importance of the customer’s voice

Bit cheesy, but i really rate this company and like there apporach to tapping into the consumer

Be more human....pleeeeease

Thanks a bunch to FutureLab and David Armano for this post. Lets never forget to be ourselves first and foremost.

How to Be More Human

This morning a couple of things came together for me. The first, was that I unfollowed a company/individual on Twitter because the volume they were producing felt automated and not human even if there were college interns manually updating it (or maybe just a script). It just didn't feel right. The second was reviewing a deck where it talked about the need for "being human" on the social web.

But it didn't get into how exactly, and that's where my gears started turning. Right now the biggest challenge to being successful on the social web is through high quality micro-interactions with high quality human beings. But organizations will find this difficult to embrace. The industrial revolution has taught us to mass produce and move away from human dependency. ATM's have replaced the need for that local bank teller in most places and call centers are known as cost centers, so companies face a bit of a problem here. But if they can figure out a way to make the numbers work, organizations who put a human face to themselves stand to become the industry leaders in a space that's still in it's early phases. Here's a few ways to be "more human".

Don't Automate
Automated interactions are done by machines and people know it. Right now, we're flocking to the social web because we can get a personal touch that cannot be gotten elsewhere. While the "masses" deal with terrible automated phone services etc, we feel privileged to be able to interact with the real people behind an organization. This presents scaling issues to the organization, but the average customer we just like it and will come back for more.

Don't Strive For Perfection
People aren't perfect, and that's expected in the social web. In fact, the more perfectly something is written, produced, or executed—the more suspicious it becomes. Communication and interactions on the social web should be similar to those in real life. Imperfect, messy, spontaneous, and occasionally personal. Zappos understands this well. After a conversation with one of their representatives from their call center, we received a handwritten note that referenced something personal that was discussed during the call. You don't get more human than that.

Talk Back
In a scene from "I Am Legend" Will Smith talks to a mannequin to try to emulate human contact. Of course this fall short and it's exactly the same dynamic that exists on the Web when organizations refuse to talk back to the people who they want to talk to. The substitute doesn't work and all that's left is something that looks alive from a distant, but really isn't.

Talk Like A Human
People can spot robots, artificial intelligence and a fake a mile away. Talking like your legal team, your PR agency or a computer will get you unfollowed, unfriended or ignored. If we wanted to hear from machines, robots or legal eagles, we'd watch more advertising or interact with your organizations mainstream touch points. We're on the social web because we want to connect with other human beings and we want them to act like them. Being human means talking like a human. Conversational style trumps dictation because human beings only dictate when we're in very specific situations. If people walked around all day dictating as opposed to being engaged in human conversations, it would come across as very odd. Interestingly enough, many organizations don't have people who know how to communicate like this. In the coming years, you may have to find some.

Avoid Artificial Additives & Preservatives
Until someone invents the perfect android, there's not much that's artificial about being a human being—we make mistakes, are fragile and the good ones know when to say "sorry" and try harder. Anything else comes across as artificial and less than human. Being more human on the social web means doing all of these things because it's likely that you'll make mistakes and that's part of the process. It's OK, because you'll be interacting with other humans who also make them. An artificial presence is unlikely to succeed because it will feel too much like the way your organization presents itself traditionally, and again—that's not why your customers are engaging on networks. They want a more human approach.


Original post found here

Myspace does reality TV

Thanks Mashabale for this latest move in Myspace land

March 25th, 2009 | by Adam Ostrow4 Comments

Now this makes sense. MySpace is getting into reality TV with a new Web-based series called “Married on MySpace” that will chronicle one couple’s journey to their wedding day, with MySpace members driving much of the decision-making in planning the event.

The process starts with couples submitting videos to MySpace and users voting on who should be featured. Once that has been determined, MySpace users vote on other aspects of the event, like selecting what the bride and groom wear, where they celebrate their bachelor and bachelorette parties, and the wedding location.

In all, there will be 13 websidoes of Married on MySpace, culminating in the selected couple’s wedding day. The series is being produced by Endemol USA, the company behind reality TV shows like Big Brother, Fear Factor, and Deal or No Deal, so the quality (or lack thereof depending on your point of view) should be up-to-par.

While MySpace () has conceded the race to be the top social networking site, it still has a place as one of the most popular entertainment destinations on the Web. Original, relatively low-cost programming like Married on MySpace that involves the community is a smart move, and something we’ll likely continue to see.

The trailer for Married on MySpace is embedded below:

Married on MySpace Trailer

Wikirank: Find What’s Trending on Wikipedia

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Thanks Mashable for this on a great tool for monitoring trends on wikipedia.

March 25th, 2009 | by Jennifer Van Grove12 Comments

Wikirank does for Wikipedia () what sites like Compete do for websites. It’s a nifty analytics tool that tracks trending topics on the world’s largest online encyclopedia, displays the 10 most read articles in the last 30 days, and gives users the ability to compare stats for up to four different topics.

Wikirank uses the actual usage data from Wikipedia servers to give visitors a better global or custom view of what’s happening across the information hub. Cooler features include the ability to graphically compare impressions on four different articles, embed graphs, view Wikipedia entries, and quickly search for related content on Google News, Twitter (), or The New York Times.

We really like Wikirank’s trending topics on the home page. Topics are ranked by percent change and certainly provide a great graphical view of major fluctuations in page views. Plus, the most read topics in the past 30 days give us an awesome glimpse at what’s hot over a longer duration.

We love the tool and can’t wait to use it to start comparing pop culture and Web trends, especially since Wikipedia has 10 million plus articles and is most likely one of the first places mainstream audiences go for information on the Web. What do you think of Wikirank? Tell us in the comments.

Social Collider - the most seriously cool, and heavyweight twitter visualisation yet

Thanks guys for the post and the work. Stunning and, just possibly, very very useful

Social Collider is a new collaboration with Sascha Pohflepp, a JavaScript visualization to reveal cross-connections between conversations on Twitter. The project launched just 2 days ago and has been commissioned by Google for their Chrome Experiments collection and was produced by the friendly peeps at Instrument. Social Collider acts as a metaphorical instrument which can be used to visualize how memes are created and how they propagate. Ideally, it might catch the Zeitgeist at work.

Concept

In December Sascha and me were both independently contacted about contributing to the Google Chrome Experiment project. We decided to rack our heads together on this one, since we both much rather liked to build something which would qualify as a browser experiment as per brief, but also could become something bigger & more worthwhile over time. In several meetings over coffee we slowly narrowed down Sascha's general visualization idea to the level of trying to show one's own data traces in context or contrast to things going on around us, which would possibly influence our moods and actions without us realizing consciously. Initially we wanted this context to be relatively removed both thematically and in terms of scale (personal vs. societal) and were thinking about plugging into energy consumption, other environmental datasets, the weather or also news headlines. The problem with the first two still is obtaining data in a sufficiently granular format to be actually meaningful (i.e. not summed values per year or aggregated per country).

Massive uptake of grassroots data portals like Usman Haque's Pachube will hopefully change that in the not too distant future. In hindsight, not focusing on the weather also proved to be a good thing since Use All Five already covered that topic with their fantastic smalltalk experiment, which is also part of the Chrome collection. Since we both have been vivid Twitter users for quite a while now, we knew that people are using it to discuss really anything, incl. the topics mentioned above. The realtime granularity combined with the ad-hoc discussion element is something I've been increasingly treasuring on Twitter because it adds personal contexts, opinions and feedbacks to the “data”, be it the weather, music, politics, geekery etc. Of course other platforms like Facebook have that too, but for our purposes Twitter was the better option since it does allow for socially far more widespread conversations (it doesn't have any concept of groups, tribes or networks. Anyone can talk & reply to anyone they wish without jumping through any hoops). It also has the benefit of well (better) thought-out APIs.

Visualization

Technically, as well as for time reasons, we decided to create a pure clientside JavaScript visualization. This decision provided a great creative challenge for us, but also limited our choice of easy-to-access compatible webservices even more. To satisfy the instant gratification part of being a browser experiment, we also had to exclude any data coming from APIs requiring 2-step authentication and we too made a conscious decision to avoid the dreaded Password Anti-pattern. The last missing key ingredient needed was a strong metaphor. As any hobby psychologist knows, good metaphors are a key enabler for (successful) visualizations. On the other hand the majority of network visualizations today are based on the ”rocks & sticks” metaphor (thanks Mike & Tom! :), basically assuming nodes as particles and connecting them with lines.

This visual language has been culturally lifted straight off mathematical graph theory text books and of course it's hard (if not impossible) to totally break free of that established mental image, especially when the data we're dealing with is literally particular (microcontent) and loosely connected. Yet to add a twist to this classic, we decided to approach the visualization more like the creation of a painting. We would use slow reveals to give the user more time to better trace all identified connections, as well as place it in a conceptual environment and use a visual language which directly references particles. With the Large Hadron Collider launch from only a few months earlier still glimmering on our mental horizons, this became the perfect (if obvious) metaphor…

Mapping

Within this space, particles are mapped two dimensionally based on their position in time (vertical axis) and search query ID (horizontally). Search results of each query are automatically connected vertically via smooth, curvy B-splines (using a JS port of this) in the same color. If results from different queries are somehow related (see below), a spiral is first drawn around the older particle but will eventually connect the other related particles horizontally.

The size of the spiral corresponds to the number of cross-connections the related message/tweet has accumulated. Hovering with the mouse pointer over particles displays their related message. Clicking on a node opens the selected tweet on twitter.com…

Data mining

Since Twitter messages have a hard limit of 140 characters, the community has come up with various syntactic sugar to add meaning & metadata. At current, there're 5 major potential connection axes in Twitter messages: @usernames, direct @-replies, #hashtags, retweets (RT), URLs posted. Using exclusively Twitter's Search API (via JSONP), we initially allow users to search for usernames, generic phrases or hashtags.

These original search results are then analyzed for each of the 5 data axes and if matched, queued for secondary search requests. As this “spidering search” is ongoing the visualization space is being decimated into columns based on the number of successful search queries. If a query did not return anything its column is being removed to maximize available screen space. Once all queries have been executed, the connections between retrieved messages are slowly revealed.

Features & Shortcomings

Any visualization has strong points and shortcomings. Our aim was to fill a current niche and provide the means to create a fairly macroscopic picture of Twitter activity, by attempting to trace how content & memes spread through the network.

Unlike the more ubiquitous line and bar charts of other Twitter visualizations, ours was supposed to give a qualitative, not necessarily quantative, overview. I also believe we have somewhat succeeded with this as these examples clearly show (click on the images to see bigger versions on flickr):

Social Collider 1 hour after launch

Social Collider 16 hours post launch

SXSW panel by John Tolva

Guardian Open Platform launch by jaggeree

BookCamp & PaperCamp weekend marked by the pink & red clusters near the top

Visually, the spirals have the effect of pen scribbles to mark hotspots, messages which have resonated in the community and have triggered re-tweets, replies or generally just kickstart a new meme (e.g. identified by a new #hashtag). The maps also show how quickly some of these trends propagate, spawning a multitude of messages in close succession (in time) and so causing clusters. However, we're also aware of various shortcomings of the visualization. These mainly become obvious when one wants to drill further down into the data. Things like filtering or zooming are not possible at the moment, but would certainly add a whole new level of functionality & usefulness… For example, the above mentioned clusters caused by events (e.g. #sxsw) or “major” news can be identified easily, but currently not easily examined without zooming functionality. Yet without attempting to sound defensive, it's good to remember this so far was primarily just a browser experiment after all… In fact, depending on the complexity of the returned data set, it's quite easy to bring your browser to its knees (especially Firefox… Sorry guys, I still love you! :).

This in turn has most likely to do with the multitude of setTimeOut() threads spawned to slowly draw the connection curves and the sheer number of nodes in the SVG canvas used to create the visualization. Creating all particle nodes (sometimes several thousands) with 3 mouse event listeners attached each doesn't help performance either! So my cheeky side is quite happy to have created a challenging environment for the browser(s) too and I honestly was blown away how well Chrome kept its calm, regardless… Furthermore there's also room for improvement on the data analysis side: Because of the various URLis.gd creator) in use, sometimes links pointing to the same URL are not matched. Also the Twitter search API is not case sensitive so it can also happen that the wrong shortened URLs are associated in secondary queries. Both issues can be overcome, but again it's one of those things we simply didn't had time to implement so far. shortners (e.g. see my own

Future plans

I'm still thinking about adding support for other fairly ubiquitous services like flickr & del.icio.us, not only because there're strong overlaps with Twitter, but also because it would give potentially interesting insights contrasting/complementing Twitter messages with photos taken at similar times or links saved on delicious, which might provide further reading to links posted on Twitter… For example, one of our plans for flickr integration was to use the fantastic Pixstatic library to create colour fields in the background of the visualization, taking the average color of each retrieved image and blending them into each other, similar in style of a heatmap visualization.

However, the stable version of Google Chrome currently hasn't got any support for ImageData access to pull off this feature. But the good news is that it's being worked on and is already implemented in the Chrome 2.0 beta version… It would be great to save & share generated visualizations by storing them in a link with original search term and timestamp, so they can be recalled anytime… (like: http://socialcollider.net/?q=from:toxi&t=1237561532) There're lots of other little ideas floating around and we're currently scoping out details how to take development further in practical terms, i.e. picking a license & hosting and preparing source code for an open source release… Please stay tuned!