This document discusses mobile image and object recognition technology. It describes how object recognition works by characterizing objects with local descriptors from interest points, and how this allows for robust identification of objects in cluttered scenes regardless of scale, orientation, noise or partial occlusion. Main applications are recognizing products from images, like CD covers, logos, and products with distinctive packaging to provide users with information like prices. The technology involves a mobile application, recognition engine, and content provider. It works by having the mobile app take an image, send it to the recognition engine which identifies the object and returns a product ID to lookup details from the content provider.

1. Mobile Image and Object Recognition
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Technological Innovation
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Technological Innovation 1

2. Image Recognition
Technological principles
• Nowadays image and video processing tries to solve
different type of problems:
-image and object recognition (computer vision)
-text recognition (statistical keyword extraction and OCR)
We focus on… - biometrics (facial recognition)
- and linear - 1D and 2D barcode decoding
How does this object recognition method work??
•Objects from the scene are characterized by local
descriptors representing appearance of these objects at
some interest points (or salient image patches).
•The interest points are extracted in a way which is
invariant to scale and rotation of objects present in the
scene.
•The salient image patches have specific and invariant
characteristics that can be stored in the database and then
compared.
Advantages??
•This method can robustly identify objects in cluttered
scenes, irrespectively on their scale, orientation, noise,
partial occlusion, and also, to a certain extend, on changes
in viewpoint and illumination.
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Technological Innovation 2

3. Image Based Search
Main applications
•This image processing technology is designed to recognize rigid or semi-rigid
objects with characteristic appearance (often with a drawing on their surface).
•Some examples are:
•CD/DVD/Book covers, pictures (e.g. showing products) from newspapers
and magazines, logos and trademarks
•indoor and outdoor posters (e.g. movie posters)
•real objects with characteristic appearance (products with characterizing
packaging, e.g. cereals box, box of milk etc.)
•Image recognition in a web page.
•In case of flat objects with some drawing (DVD covers, books, posters) only one
reference picture has to be stored in the database.
•In the case of "truly 3D" objects several reference views need to be stored.
•Through different test with the types of objects mentioned above the developed
technology is able to provide an enhanced recognition accuracy (improving other
techniques output)
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Technological Innovation 3

4. Image Recognition
Technologies involved+ Architecture
JavaME Mobile Application Developt under LWUIT (Lightweight user interface
toolkit) Using Standards APIs
LWUIT have been developts by Sun. It´s MIDP2/CLDC1.1 compliance and
solves some portability/fragmentation Problems. It´s open source with
license “GPL + classpath exception
Mobile Application Service Logic Recognition Engine
Content Provider
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5. Image Recognition
Flows
8. Mobile Application show the final results.
-General Info (prices, details..)
- Offers 4. Recognition Engine Recognizes
- etc… the Object and Returns Product
ID.
Image/ video
Image/video
5. Product ID
1. User Open Mobile Application Proxy server Recognition Engine
2. Mobile Application Connect 6. ID product 7.a. Product Information
Camera and takes Image/Video Search
7.b. Comercial actions: Price,Address,Offers
3. Mobile Application sents
etc…
Image/Video.
Content Provider Web
Services
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Technological Innovation 5

6. Mobile Application
Overview
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Technological Innovation 6

7. TELEFÓNICA ESPAÑA
Technological Innovation 7