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In concluding this survey, we should highlight the fact that the technologies for imagerecognition are the key element for supporting mobile image search. Around this key element,different purpose applications have been developed focusing on shopping, entertainment,tourism, advertising, finding the cheapest or the most convenient option, etc. Concerning theemployed business model the majority of the existing companies doing business in this marketfollow a monetary benefits approach where revenue streams are generated either by the

contracts signed in the context of a certain advertising campaign, or by charging fees on thebasis of a SaaS-based model, or both. However, this is expected to change as the imagerecognition technology evolves favoring a business model, where profit is not derived directlyfrom selling the image search functionality but from capitalizing the users loyalty and trustestablished in using the search application (e.g. advertising-based model). Moreover, we shouldhighlight the importance of the client interface in attracting new users and the observedtendency in incorporating augmented reality technologies as an integral part of mobile imagesearch services. Finally, we can also predict that the constantly growing interest around themobile photo sharing applications and AR applications will soon motivate the mobile image

search companies to enhance5. Conclusions and FutureWorksIn this paper, we explored the potential of web search with

mobile images using both images and text. We have shownit is possible to conduct fast and comprehensive CBIR over

hundreds of millions of images using a text-based search engineon keywords generated from an initial search. We presented

an approach to recognizing location from mobile devicesusing image-based web search, and showed that common

image search metrics can match images captured witha camera-equipped mobile device to images found on the

5these applications with image-based searchinA hybrid image-and-keyword searchingtechnique was

developed that first performed an image-based search overimages and links to their source web pages in a bootstrap

database that indexes only a small fraction of the web anda simple frequency-based procedure was employed to extract

relevant keywords from these web pages. These keywordscan be submitted to an existing text-based search engine

(e.g. Google) that indexes a much larger portion of theweb. The resulting image set is then filtered to retain images

close to the original query. It is thus possible to efficiently

search hundreds of millions of images, retrieving those thatare not only textually related but also visually relevant. Wedemonstrated our approach on an application allowing users

to search information on the web by matching images.In the future, we would like to explore more sophisticated

image matching techniques and adapt them to the

landmark image domain. In addition, we plan to carry out

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an extensive quantitative evaluation of our approach and an

overall usability user study of the system.g functionalities.

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Executive Summary

The objective of this document is to survey the existing applications for visual-basedmobile image search and investigate their technical and socio-economic aspects. Tothis end, we go through the basic architecture of these applications and list the utilizedtechnologies. Moreover, we provide an overview of the user needs and usage patternsof such applications, as well as a brief description of the business models that arecurrently employed. The most significant part of the document is devoted on presenting12 of such mobile image search applications, where for each one we provide briefbackground information, we describe the functionality of the offered service and the

domain of target users, and we discuss the adopted business model. In concluding, wecompare the examined applications in terms of the adopted technology, target usersand business model and identify the most important trends in the sector both from atechnological and socio-economic perspective.

1. Introduction

The mobile search industry is almost as old as the telecom industry and its primalobjective is to enable people to find location-based services by entering a word orphrase on their phone. An example of usage would be a person looking for a local hotel

after a tiring journey or taxi company after a night out. The services can also come witha map and directions to help the user. With the years, mobile content has changed itsmedia direction towards mobile multimedia. Starting with keyword-based search andgoing through the step of voice search, now the end user is offered the functionality tocapture a photo in his cell phone and find relevant information on the Internet. Visual-based search works like traditional search engines but without having to type any text orgo through complicated menus. Instead, users simply turn their phone camera towardsthe item of interest and the mobile search engine returns relevant content based on itsinterpretation of the users visual query. Despite the many similarities, mobile search isnot just a simple shift of PC web search to mobile equipment since it is connected tospecialized segments of mobile broadband and mobile content, both of which have

been fast-paced evolving recently [8].

High-end mobile phones have developed into capable computational devices equippedwith high-quality color displays, high resolution digital cameras, and real-time hardware-accelerated 3D graphics. They can also exchange information over broadband dataconnections, sense location using GPS, and sense the direction using accelerometersand an electronic compass. All these functionalities enabled a new class of augmentedreality applications which use the phone camera to initiate search queries about objects

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in visual proximity to the user. Pointing with a camera provides a natural way ofindicating ones interest and browsing information available at a particular location.Once the system recognizes the users target it can provide further information (themenu or customer ratings of a restaurant) or services (reserve a table and invite friendsfor a dinner) [1],allowing to link between the physical and the digital world [2]. In this

context, visual search has been extensively researched in recent years [3], integratingmobile augmented reality [4]and outdoor coordinate systems [1] with visual searchtechnology.

One advantage of mobile visual search is that it is way faster than conventionalsearching methods. The reason for this is that even highly typists who manage up to900 characters per minute on the PC keyboard start working at a very low pace when itcomes to cramped keyboards and touch screens on mobile phones. Typing with allfingers becomes almost impossible, but capturing and sending an image just takes afew seconds. Moreover, people may prefer snapping a photo than using words todescribe its content, especially when the object of interest is difficult to describe in

words, for example when pointing to an unknown edifice. Thus, a mobile search enginethat will allow visual search might have easier time finding an audience.

According to [7], in 2006, smartphones accounted only for 6.9% of the total market,while in 2007 the market segment reached 10.6%. The total annual sales of mobiledevices reached 1,275 million units in 2008, with 71% of them sold with data facilities, ofwhich 15% (of total sales) correspond to smartphones. In Europe, 280 million units weresold in 2008, of which 19.3% where smartphones and 65.5% enhanced devices. It isevident that the camera-enhanced, hand-held devices are being spread at a very fastpace.

Moreover, according to a leading market research firm eMarketer, by 2011, mobilesearch is expected to account for around $715 million. According to a recentstudy(April2011) from Google conducted by Ipsos OTX, an independent market research firm,among 5,013 US adult smartphone Internet users at the end of 2010, 71% ofsmartphone users search because of an ad theyve seen either online or offline; 82% ofsmartphone users notice mobile ads, 74% of smartphone shoppers make a purchase asa result of using their smartphones to help with shopping, and 88% of those who lookfor local information on their smartphones take action within a day. Earlier this year,Performics predicted that mobile search would soon reach 10 percent of all the searchimpressions its clients were seeing. In the end of April 2011 the firm said that mobileimpressions accounted for 10.2 percent of all paid search impressions (desktop +mobile).

These and other recent studies clearly show signs that mobile search is movingmainstream and gaining momentum. Unfortunately, as far as we are aware, there areno figures about the size and dynamics of the image-based mobile search segment ofthe market. However, we can reasonably expect that the segment of mobile imagesearch will scale proportionally to mobile search, creating new opportunities and offers.This is also advocated by the fact that major players in the mobile communication and

http://www.emarketer.com/http://www.emarketer.com/http://googlemobileads.blogspot.com/2011/04/smartphone-user-study-shows-mobile.htmlhttp://googlemobileads.blogspot.com/2011/04/smartphone-user-study-shows-mobile.htmlhttp://googlemobileads.blogspot.com/2011/04/smartphone-user-study-shows-mobile.htmlhttp://blog.performics.com/search/2011/04/mobile-paid-search-impression-share-crosses-10-threshold.htmlhttp://blog.performics.com/search/2011/04/mobile-paid-search-impression-share-crosses-10-threshold.htmlhttp://blog.performics.com/search/2011/04/mobile-paid-search-impression-share-crosses-10-threshold.htmlhttp://blog.performics.com/search/2011/04/mobile-paid-search-impression-share-crosses-10-threshold.htmlhttp://blog.performics.com/search/2011/04/mobile-paid-search-impression-share-crosses-10-threshold.htmlhttp://blog.performics.com/search/2011/04/mobile-paid-search-impression-share-crosses-10-threshold.htmlhttp://blog.performics.com/search/2011/04/mobile-paid-search-impression-share-crosses-10-threshold.htmlhttp://blog.performics.com/search/2011/04/mobile-paid-search-impression-share-crosses-10-threshold.htmlhttp://googlemobileads.blogspot.com/2011/04/smartphone-user-study-shows-mobile.htmlhttp://www.emarketer.com/

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search industry like Nokia and Google, are investing a lot of effort in the mobile imagesearch concept and are aggressively trying to create applications and relationships inorder to take advantage of the mobile ad market.

DISADVANTA

Under the client-server architecture, a user has to snap a picture, submit it to theserver and then have it recognized. Maintaining an upstream IP connection is still

challenging on the phone network. The user might wait too long and lose

patience. The recognition could fail for many reasons, for example, the image is

too dark, too blurry or simply because the captured object is not in the database.

When recognition fails, the user has to snap another picture and submit it again.

After a couple of rounds, the frustrated user can believe the system does not

work. GES