Time: Tuesday 6:25 –
Professor: Xin Chen, Ph.D. Senior
Research Scientist at NAVTEQ
Geospatial information has become ubiquitous in everyday life, as
evidenced by on-line mapping services such as Microsoft Virtual
Earth/Bing Map, the recent addition of "place" features
on social network websites such as Facebook, and free navigation
on Nokia smart phones. Behind the scenes is digital map content
engineering that enables all types of location-based services.
Course material will be drawn from the instructor's research
experience at NAVTEQ, the Chicago-based leading global provider of
digital map, traffic and location data. This course will provide
comprehensive treatment of computer vision, image processing and
visualization techniques in the context of digital mapping, global
positioning and sensing, next generation map making, and
three-dimensional map content creations. Real world problems and
data and on-site industry visits will comprise part of the course
Lunch and Learn at NAVTEQ
Headquarters on December 3, 2010
CTO Amreesh Modi shares his insights on the
geospatial industry with Geospatial Vision and Visualization
Geospatial Vision and Visualization students get a
behind-the-scenes look at NAVTEQ True, the next generation mapping
Professor Xin Chen, a Senior Research Scientist at
NAVTEQ, welcomes Geospatial Vision and Visualization
students to NAVTEQ.
Geospatial Vision and Visualization students network
with NAVTEQ R&D members.
Geospatial Vision and Visualization students toured
the traffic studio that houses NBC Channel five and several radio
stations including National Public Radio (NPR) and local celebrity
Geospatial Vision and Visualization students present
their final course projects to CTO, Amreesh Modi and R&D
senior managers and staff.
Featured Final Course Projects (Each
of the 24 students was able to develop a final project within a
Real-time City-scale LIDAR Rendering
Hongwen Huai and Hongwu Huai
This project is to render city scale LIDAR 3D
point cloud in real time. The challenges are limited system and
video memories and lack of computation capabilities on consumer
level graphics cards. We implement streaming by searching,
loading, saving and rendering all the visible data from the
original 80GB raw data. Level of Detail (LoD), camera culling,
Octree and Kdtree are implemented in the pipeline.
Hole Filling for 3D LIDAR Point Cloud
Geospatial information is obtained by their
acquisition devices like panaroma camera and LiDAR scanner. The
data obtained by 3D scanner, after registered is a scene of
real world which is composed by 3D point cloud. However,
because of many unpredictable reasons like running car,
accuracy of scanner and occlusion, the scene is always noisy
and contains some holes in it. So in this project, we address
the problem of post-processing of street view LiDAR data, and
try to fill the hole appearing on the road.
Color Infrared Satellite Photo Feature
In this project, we will extract and classify
feature from color infrared satellite/aerial image. First, we
will briefly talk about the purpose of this project. Next, we
will illustrate the methods of classification. Finally, we will
show and assess the results as well as give some advices on
Syeda Fatima Rizvi, Het Joshi, Asad Akram
This porject implements a prototype of
Indoor Navigation system. we survey Galvin Library at IIT; map
it to grid object; gather information relating to grid object;
use panorama and navigation algorithm to get directions within
the building. we applied what we learned in this course.
Indoor Virtual Tour
Qi Zhao, Jiayu Ji, Peng Yao
This project is to develop a system which is
able to provide panoramic view of a pecific building. It is a
web-based system so that it can be run on different platform.
Also, it will provide maintainability which allow user to
maintain the panoramic photos and floor map themselves. Due to
the time constraint, we collect data from Stuart Building only
to test the system.
Cell Phone Probes for ADAS
Aravind Lekshminarayanan, Kamalesh Kumar, Reda
The main goal of our project is to model the
road geometry from cell phone probe data so as to be used in
ADAS systems. The road geometry includes vertical slopes and
horizontal curvatures. The given probe data are recordings from
a large number of cell phones with latitude, longitude,
elevation and other information, as well as the ground truth
from GPS+IMU data collection. So, the objective is to derive
the road geometry automatically using only the probe data or
both probe data and maps.
Dipti Sharma, Hema B.S., Sugar LanCrét
In this project we have implemented an object
detector that detects stop signs and license plates in static
pictures as well as in live video. This project is implemented
mainly using the SURF (Speeded Up Robust Features) algorithm
which is a robust image detector & descriptor. In the
process of implementing an object detector, we also studied
about other object detection algorithms like template match and
Haar-based object detection. This report includes a detailed
description of the working mechanism of these three algorithms
and discusses the pros and cons of each. This is followed by
the workflow and architecture of our object detector
LBS Survey and Application
This project is to survey the current state of
location based services in the U.S.. We proposed and
implemented a novel LBS applicaiton on IPhone. In contrast to
PlanCast, our application logs the events that have happened.
This project is to implement a scene photos
morphing software. Before morphing, the two warping processes
are needed by two source images separately. In the program,
users could interactively choose a set of control points in two
pictures respectively, and also could choose the intersteps
warping process needed, meanwhile in every run, the control
points could be saved as a file.
This project tested object detection algorithm
SIFT by experimenting variations of geometric, localization,
rotation, resolution, lighting, noise and object types.
Guest Lecture: Learning from Founding a
Geospatial Startup by Zhong Chen, Founder and President
of Dynasty Group, November 9, 2010
Zhong shares his entrepreneurial experience with
Geospatial Vision and Visualization students.
Zhong presents his “dream car” for
mobile data collection.