Presentation on theme: "By Zheng Sun, Aveek Purohit, Shijia Pan, Frank Mokaya, Raja Bose, and Pei Zhang final38.pdf."— Presentation transcript:
By Zheng Sun, Aveek Purohit, Shijia Pan, Frank Mokaya, Raja Bose, and Pei Zhang http://www.hotmobile.org/2012/papers/HotMobile12- final38.pdf
Purpose Problem: Digital Compass readings inside are disrupted by metallic objects GOAL: Increase indoor environment digital compass orientation readings with ceiling pictures
Sensors / Hardware Utilized Digital Compass Sensor - provides the orientation of the device relative to the magnetic north of the earth Camera – Used to take pictures of the ceiling Accelerometer – Check phone orientation
This system is dependent on different observations such a ceiling panels and the straight lines made by those titles but can be some problems when it comes to lights, vents, and other things on the ceiling but they are dealt with by using histogram equalization and multiple edge detection techniques to detect straight lines.
Polaris uses Straight line of the panels and other edges it gets pictures of. The features of the panels and other objects that it looks at are the parallel lines of the edges
How-to Aggregating ceiling pictures through crowdsourcing Extracting effective ceiling patterns Using patterns and raw compass readings taken at the time of the picture Inviting people that work in the same building to offer pictures to the system
Crowd Sourcing When people who choose to participate in the crowdsourcing activity are in their indoor environments, they will be prompted to contribute ceiling pictures to Polaris This is aided by our observation that unobstructed pictures of the ceiling are easily obtainable using the front camera on mobile phones during the users normal interaction with the device.
Orientation The software needs pictures when the phone is held horizontally by the user and take pictures as automatically Uses the accelerometers to make sure the phone is horizontal by measuring 3d accelerations
Extracting Effective Patterns Use a Histogram equalization tech. Convert the image to grayscale Detect the edge with edge detecting algorithms By the lines on the ceilings and the raw digital compass data the orientation polaris comes up with an orientation that is closest to raw compass reading as the final orientation
Conclusion Overall the readings inside increased digital compass readings in an indoor environment Polaris achieved a 4.5 degree average orientation accuracy which is 3.5 time better than raw readings