CSc Senior Capstone Sequence 2004-2005
Computer Science - The City College of New York
Vision, Video and Virtual Reality
Instructor: Professor Zhigang Zhu
Augmented New York City - Vision,Video and Virtual Reality
in Traffic and Surveillance
Widely distributed sensor networks are becoming commonplace in our
environments. Web-available cameras allow anyone with an Internet
connection to peek in real-time into traffic, national parks, sporting
events, and office spaces; security guards have access to tens or hundreds
of cameras; and robot explorers carry cameras and other sensors into dangerous
or out-of-reach areas. As a concrete example in one of the world’s
largest cities, New York City DOT’s Traffic Management Center maintains
86 closed circuit TV cameras on major arteries of NYC trying to disentangle
traffic jams. With an Intelligent Transportation Systems (ITS), the cameras
and signals are controlled by operations staff using interfaces of projection
graphics and arrays of video monitors in order to track and manage the system.
DOT’s Real-Time Traffic Cameras provide online (http://nyctmc.org)) both streaming
video and frequently updated still images from DOT camera locations for traffic
advisory. A user (driver) can click the corresponding location of the camera
in a top-view 2D map to activate a video stream or still images. In the City
Drive Live program, twenty-two of DOT’s traffic cameras, showing live traffic
conditions at major locations, can be watched on TV on Crosswalks Channel
74, the television network of the City of New York, on weekday mornings from
6:30 to 9:00 am. The program first slides a 2D map with camera locations marked,
and then shows each video stream for a while, in a certain order.
However, the individual sensors (cameras) generally provide constrained
and separate viewpoints from which users experience the spatially disparate
information. This limits the ability of users to immerse themselves in
the experience provided by the space, to construct coherent models of
the spatial geometry, and (in appropriate circumstances) to make real-time
tactical decisions. We are interested in an augmented interface for real-time
traffic cameras, where the video streams of the real traffic cameras are
geo-registered with a 2D map or even a virtual 3D model of the streets and
buildings of the city. A user could make a virtual walk-though in the augmented
and immersive environment, viewing the real-time traffic from the sensor
network.
Requirements: In this project you are suppose to have part
of the 22 NYC DOT video streams registered on a NYC map, and implement
a real-time virtual walkthrough. For doing that, you need to (1) register
each camera view with the 2D map using planar transformation; and (2)
the system can change viewpoint to let us virtually walk or fly through
the map and view the real video with right view angles.
Tools: A 3D rendering system (OpenGL, Java 3D or other rendering
tools).
Input: several traffic video sequences (for example segquence 1), and
a 2D map
New video sequences in AVI (each from 5MB to 16MB, approximatly 30 seconds
to 1.5 minutes, images 720*480 in color ):
Location 1 (time
1, time 2)
Location 2 (time
1, time 2)
Location 3 (time
1, time 2)
Location 4 (time
1, time 2)
Location 5 (time
1, time 2)
Output: a system that can display the augmented NYC map
(1) Study rendering tools (with C++)
(2) Change viewpoints of a 2D map (Matlab)
(3) Align video on the map (Matlab)
Reading: OpenGL, Java 3D, planar transformation (lecture slides).
Copyright @ Zhigang
Zhu (email zhu@cs.ccny.cuny.edu ),
2004.