Android Project
Transcript of Android Project
KANARA COLLEGE SOCITY’SSHREE VIDYADHIRAJ POLYTECHNIC
KUMTA-581343(U.K)
DEPARTMENT OFCOMPUTER SCIENCE ENGINEERING
2013-2014
PROJECT REPORT ON
Android Augmented RealitySubmitted In Partial Fulfillment of the Requirement of the
Award of Diploma InCOMPUTER SCIENCE ENGINEERING
UNDER THE GUIDENCE OF
SHRI DINESH BALGI
SUBMITTED BY
Gurushankar S G 370cs11012Shaikh Ayeed 370cs11044Nireeksha Nayak 370cs11027
Spoorti Jain 370cs11048B L Spoorti 370cs11008Spoorti Kalmane 370cs11046
Under the curriculum and syllabus of The Board of Technical Examination Bangalore
(Government of Karnataka)
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Android Augmented RealityKANARA COLLEGE
SOCIETY’SSHREE VIDYADHIRAJ POLYTECHNIC
KUMTA-581343, UTTARA KANNADAKARNATAKA
Department of computer science & Engineering
CERTIFICATE
Certified that the project on “ANDROID AUGMENTED REALITY” is a bonafide work carried out by GURUSHANKAR S.G, SHAIKH AYEED, NIREEKSHA NAYAK, SPOORTIJAIN, B.L SPOORTI,
SPOORTI KALMANE In partial fulfillment for the award of Diploma in computer science &engineering course of DIRECTORATE OF TECHNICAL EDUCATION, Bangalore during the year 2013-2014.The project report has been approved as it satisfies the academic requirements in respect of project for the diploma course.
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Signature of the guide Signature of the HOD
EXTERNAL VIVAName of the ExaminersSignature with Date
1. ________________________ ____________________
2. _________________________ ____________________
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MEMBERS OF OUR TEAM:
Gurushankar S.G 370cs11012Shaikh Ayeed 370cs11044Nireeksha Nayak 370cs11027Spoorti Jain 370cs11048B.L Spoorti 370cs11008Spoorti Kalmane 370cs11046
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ABSTRACT
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ACKNOWLEDGEMENT
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Table of Contents
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1. INTRODUCTION
Augmented Reality (AR) intends to provide richer experiences by overlying
labels or virtual objects over the scene observed through a camera attached to a
computer. Many AR systems follow the approach of analyzing in real time the
video stream provided by a camera to recognize objects. This way they figure
out what virtual objects must be drawn, and where, overlaid to the video stream.
These systems need a model of the world to match against the video stream.
Advances in the HW have made it possible to perform this computationally
expensive image processing in mobile phones, although no commercial system
has yet appeared, and only controlled demonstrations have been shown.
By using sensors such as accelerometers, GPS and digital compasses
available in mobile phones such as the Android devices, an alternative approach
can be followed to augment the reality perceived through the camera in mobile
phones. The information provided by these sensors can be used to know where
the mobile is located and towards where it is oriented. Nearby geo-tagged labels
found in the vicinity of the scene can be found in a database of POIs and then
shown on the screen on top of the object to which they are associated, without
requiring intensive image processing.
It is well known that the A-GPS of these devices can report big offsets from
the actual position, but compared to visual AR approaches, it is available
everywhere outdoors and does not require a model of the world to match
against, being also immune to moving objects that can a
affect visual approaches. Digital compass can also report significant errors, but
it provides good enough orientation information for many applications that users
of mobile phones desire to use.
Nowadays Maps are increasingly being used from mobile phones. These
have big touch screens and powerful microprocessors, but it is specially the geo-
location information provided by GPS, and the orientation information provided
by compass and accelerometers, which enables new interesting functionality of
mobile maps that is also available in the desktop. We are developing a FLOSS
implementation of a mobile location browser using augmented reality called
RealityView whose client side runs on Android and communicates through a
Google API with the backend.
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1.1. Problem Definition(intr)
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1.2. History(augmented rea in intro)
1.3. Scope(intro)
1.4. Need of the application(intr0)
1.5. High level Design(1st overall architecture of App block
diagram in design,can be removed)
1.6. UML diagrams
1.7. Implementation(after design before program code) how it is
implemented.major algorithm
1.8. Testing (use cases, Expected behaviors)
1.9. Results
1.10. Conclusion
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2. OBJECTIVE
What is to be achieved?
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3. ENVIRONMET USED
3.1. Platform Requirement – For Development
3.1.1. Minimum Hardware Requirement
Processor : Intel Dual Core or Higher / AMD
RAM : 1GB
HDD : 1GB
1.1.1. Minimum Software Requirement
Operating System : Windows XP or Higher / Mac / Linux
Development Tools : Eclipse IDE, Android SDK, JRE 1.7
UML modeling tool : UML lab, Argouml, ObjectAid UML
1.1. Platform Requirement – For Deployment
1.1.1. Minimum Hardware Requirement
Processor : 800MHZ processor or Higher
RAM : 512MB or Higher (10mb for execution)
Internal Memory : 512MB (only 60kb is needed for the app)
Sensors : Accelerometer, GPS, compass
1.1.1. Minimum Software Requirement
Operating System : Android 2.3 or higher
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1. ANALYSIS DOCUMENT
1.1. System Requirement Analysis ( requirement for the
software)features,what is required.
1.2. Information Gathering ( about android with architecture ,
Literature survey (describe about andriod , app
development,existing implementations, existing apps)
1.3. System Feasibility
1.3.1. Economic Feasibility
1.3.2. Technical Feasibility
1.3.3. Behavioral Feasibility
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