NTW Logo (Black)

About IEEE

IEEE Membership

Products and Services

Conferences

IEEE Organizations

 

IEEE Nav Bar

 


 

 

https://www.ieee.org/graphics/onepixel.gif

https://www.ieee.org/graphics/onepixel.gif

 

IEEE Signal Processing Society Santa Clara Valley Chapter


https://www.ieee.org/graphics/onepixel.gif

https://www.ieee.org/graphics/onepixel.gif

 

 


Click here for see the full list of upcoming events.


Thursday, October 06, 2016

Indoor and Outdoor Image based Localization for mobile devices

This event is hosted/sponsored by IEEE SPS Chapter and co-sponsored by IEEE ITS, SSCS, CES & WIE Chapters.


Speakers :

   Prof. Avideh Zakhor

   EECS Department, UC Berkeley and Indoor Reality

 

Location:

   AMD Commons C-6/7/8, 991 Stewart Dr., Sunnyvale, CA (map or Google Maps)

 

Schedule:

   6:30pm: Networking/Light Dinner

   7:00pm: Announcements

   7:05pm: Presentation

   8:15pm: Adjourn

 

Cost:

   Free. Donation accepted for food.

 

Abstract:

Image geo-location has a wide variety of applications in GPS denied environments such as indoors, as well as error prone outdoor environments where GPS signal is unreliable. Besides accuracy, an inherent advantage of image based localization is recovery of orientation as well as position. This could be important in applications such as navigation and augmented reality. In this talk, I describe a number of indoor and outdoor image based localization approaches and characterize their performance in a variety of scenarios. I start with a basic divide and conquer photo-matching strategy for large area outdoor localization and show its superior performance over compass and GPS on today's cell phones; I characterize the performance of this system for a 30,000 image database for Oakland, CA as well as 5 million image database for 10,000 square km area in Taiwan. Next I describe a fast, automated methodology for Simultaneous Multi-modal fingerprinting And Physical mapping (SMAP) of indoor environments to be used for indoor positioning. The sensor modalities consist of images, WiFi and magnetic. I show that one shot, static image based localization has 50 percentile error of less than 1 meter and 85 percentile error of less than 2 meters. Finally, I describe the associated multi-modal indoor positioning algorithms for dynamic tracking of users and show that they outperform uni-modal schemes based on WiFi alone. Future work consists of demonstrating the scheme on wearable devices such as the Glass, and the Watch.



Biography:

Avideh Zakhor is currently Qualcomm Chair and professor in EECS at U.C. Berkeley. Her areas of interest include theories and applications of signal, image and video processing and 3D computer vision. She has won a number of best paper awards, including the IEEE Signal Processing Society in 1997 and 2009, IEEE Circuits and Systems Society in 1997 and 1999, IEEE Solid Circuits Society in 2008. She was a Hertz fellow from 1984 to 1988 and received the Presidential Young Investigators (PYI) award in 1992. In 2001, she was elected as IEEE fellow. She co-founded OPC technology in 1996, which was later by Mentor Graphics (Nasdaq: MENT) in 1998, and UrbanScan Inc. in 2005 which was acquired by Google in 2007. She founded Indoor Reality in 2015 to develop technologies for fast, automated 3D mapping and positioning of building interiors.









Subscribe to future announcements: link


 

https://www.ieee.org/graphics/onepixel.gif