The following projects are presented in alphabetical order on the supervisor's last name:

Supervisor: James Elder

Requirements: Good facility with applied mathematics

Description

To provide visual surveillance over a large environment, many surveillance cameras are typically deployed at widely dispersed locations. Making sense of activities within the monitored space requires security personnel to map multiple events observed on two-dimensional security monitors to the three-dimensional scene under surveillance. The cognitive load entailed rises quickly as the number of cameras, complexity of the scene and amount of traffic increases.

This problem can be addressed by automatically pre-mapping two-dimensional surveillance video data into three-dimensional coordinates. Rendering the data directly in three dimensions can potentially lighten the cognitive load of security personnel and make human activities more immediately interpretable.

Mapping surveillance video to three-dimensional coordinates requires construction of a virtual model of the three-dimensional scene. Such a model could be obtained by survey (e.g., using LIDAR), but the cost and time required for each site would severely limit deployment. Wide-baseline uncalibrated stereo methods are developing and have potential utility, but require careful sensor placement, and the difficulty of the correspondence problem limits reliability.

This project will investigate a monocular method for inferring three-dimensional context for video surveillance. The method will make use of the fact that most urban scenes obey the so-called “Manhattan-world” assumption, viz., a large proportion of the major surfaces in the scene are rectangles aligned with a three-dimensional Cartesian grid (Coughlan & Yuille, 2003). This regularity provides strong linear perspective cues that can potentially be used to automatically infer three-dimensional models of the major surfaces in the scene (up to a scale factor). These models can then be used to construct a virtual environment in which to render models of human activities in the scene.

Although the Manhattan world assumption provides powerful constraints, there are many technical challenges that must be overcome before a working prototype can be demonstrated. The prototype requires six stages of processing: 1)The major lines in each video frame are detected. 2) These lines are grouped into quadrilaterals projecting from the major surface rectangles of the scene. 3) The geometry of linear perspective and the Manhattan world constraint are exploited to estimate the three-dimensional attitude of the rectangles from which these quadrilaterals project. 4) Trihedral junctions are used to infer three-dimensional surface contact and ordinal depth relationships between these surfaces. 5) The estimated surfaces are rendered in three-dimensions. 6) Human activities are tracked and rendered within this virtual three-dimensional world.

The student will work closely with graduate students and postdoctoral fellows at York University, as well as researchers at other institutions involved in the project. The student will develop skills in using MATLAB, a very useful mathematical programming environment, and develop an understanding of basic topics in image processing and vision.

For more information on the laboratory: http://www.elderlab.yorku.ca

Supervisor: James Elder

Requirements: Good facility with applied mathematics

Description

Facilities planning at both city (e.g., Toronto) and institutional (e.g., York University) scales requires accurate data on the flow of people and vehicles throughout the environment. Acquiring these data can require the costly deployment of specialized equipment and people, and this effort must be renewed at regular intervals for the data to be relevant.

The density of permanent urban video surveillance camera installations has increased dramatically over the last several years. These systems provide a potential source of low-cost data from which flows can be estimated for planning purposes.

This project will explore the use of computer vision algorithms for the automatic estimation of pedestrian and vehicle flows from video surveillance data. The ultimate goal is to provide planners with accurate, continuous, up-to-date information on facility usage to help guide planning.

The student will work closely with graduate students and postdoctoral fellows at York University, as well as researchers at other institutions involved in the project. The student will develop skills in using MATLAB, a very useful mathematical programming environment, and develop an understanding of basic topics in image processing and vision.

For more information on the laboratory: http://www.elderlab.yorku.ca

Supervisor: James Elder

Requirements: Interest in both hardware and software design at the systems level.

Description

Low-cost three-dimensional face-scanning systems have a large range of potential applications in security and retail markets. Our laboratory at York University has recently developed a prototype face-scanning system that has the potential for very low-cost mass production. This project involves the development of a second-stage prototype that is one-step closer to commercialization.

The project will involve systems design and development of a specialized real-time 3D face scanner. A combination of hardware and software design will be required. The student will work closely with graduate students and postdoctoral fellows at York University, as well as researchers at other institutions involved in the project. The student will develop skills in both hardware and software design, as well as computer-vision techniques.

For more information on the laboratory: http://www.elderlab.yorku.ca

Supervisor: Franck van Breugel

Required background: General prerequisites

Recommended background: N/A

Description

CUDA stands for “compute unified device architecture.” It is an architecture to program multicore graphical processing units (GPUs for short). In the past, these GPUs were only used for graphics. However, CUDA allows us to use these GPUs for other types of computation. Since today's GPUs have hundreds of cores, algorithms can be parallelized and, hence, run often much faster.

The aim of this project is to get familiar with GPUs and to study how to program them.

More details can be found at: http://www.cse.yorku.ca/~franck/projects/cuda.html (this link is only accessible from machines within the domain yorku.ca.)

Supervisor: Andy Mirzaian

Required background: General prerequisites

Recommended background: CSE 3101

Description

The URL for Algorithmics Animation Workshop (AAW) is http://www.cs.yorku.ca/~aaw. The main purpose of AAW is to be a pedagogical tool by providing animation of important algorithms and data structures in computer science, especially those studied in courses CSE 3101, 4101, 5101, 6114, 6111. This is an open ended project in the sense that more animations can be added to this site over time.

Supervisor: John Amanatides

Required background: General prerequisites

Recommended background: CSE 3221, CSE 3214

Description

Digital signs are increasingly used in many modern buildings to direct people to appropriate rooms for meetings, services, etc. Unfortunately, “programming” them is non-trivial, especially for non-technical people such as administrative staff. The goal of this project is to make using digital signs much easier for such people.

One way to do this is to utilize what administrative staff are really good at: dealing with calendars. By assigning calendars to individual rooms/organizations/events, and having the digital signage software interpret this calendar data to display the day's events, an easier-to-use signage system can be developed.

More specifically, the deliverables of this project include a digital signage system for Bethune College. Some of the technologies that you will be expected to learn/use include Javascript, JQuery, HTML, CSS, and ical/CalDAV. We expect to go open source with this software so that others can use it as well. The deliverables will also include an analysis of what it takes to scale this type of signage campus wide, including provisions for campus alerts/emergency announcements.

Supervisor: Scott MacKenzie

Required Background: General 4080 prerequisites, CSE3461, and (preferably) CSE4441

Recommended Background: Interest in user interfaces and human-computer interaction (HCI). Understanding of experiment design. Experience in doing user studies.

Please click here for full description.

Supervisor: Scott MacKenzie

Required Background: General 4080 prerequisites, CSE3461, and (preferably) CSE4441

Recommended Background: Interest in user interfaces and human-computer interaction (HCI). Understanding of experiment design. Experience in doing user studies.

Please click here for full description.

Supervisor: Burton Ma

Required background: General prerequisites

Recommended background: N/A

Description

A fundamental step in computer-assisted surgery is registration where the anatomy of the patient is matched to an image or model of the anatomy. For some types of orthopaedic procedures, registration is performed by digitizing the locations of points on the surface of a bone and matching the point locations to the surface of a model of the bone. Here, a surgeon uses a pointer that is tracked using an optical tracking system to measure registration point locations on a patient. A registration algorithm is used to compute the transformation that best matches the points to a model of the anatomy.

Virtual navigational information (such as where to drill or cut the bone) can be provided to the surgeon after the registration transformation has been established. Here, a surgeon is using a tracked surgical drill to drill a hole along a pre-operatively defined path. Notice that the surgeon looks at the virtual navigational information instead of the patient when performing this task.

Computer-assisted surgical navigation depends on having an accurate registration. If the estimated registration is inaccurate then the navigational information will also be inaccurate, which may lead to errors in the surgical procedure. It is of great interest to know the accuracy of the estimated registration.

Further details on the project can be found here.

Supervisor: Wolfgang Stuerzlinger

Required Background: General CSE4080 prerequisites

Recommended Background: CSE3431 or equivalent

Description

Tangible user interfaces provide the user with object that they can touch and use as input devices. One example is the use of (tracked) toy houses to perform a city planning task on a large surface. This project implements a new form of tracking/identification scheme for tangible objects via LED arrays mounted on them. Furthermore, and using robotic components, the tangible objects will have the ability to move around autonomously, which enables important functionalities such as undo and replay.

Supervisor: Wolfgang Stuerzlinger

Required Background: General CSE4080 prerequisites

Recommended Background: CSE3461

Description

Many graphics programs implement snapping to facilitate drawing. Snapping ensures that end-points of lines meet, that the endpoint of one line correctly “touches” another, that objects align side-to-side, etc. One problem of simple snapping techniques is that one cannot position objects arbitrarily close together - otherwise the snapping technique interferes. A novel snapping technique “Snap-and-Go” circumvents this problem by slowing the cursor over the line, instead of snapping it close to the line. The objective of this project is to implement several snapping techniques for two-dimensional drawing systems and then to perform an evaluation with a small user study.

Supervisor: Wolfgang Stuerzlinger

Required Background: General CSE4080 prerequisites

Recommended Background: CSE3431 or equivalent

Description

Previous work by the supervisor resulted in a novel and highly accurate Virtual Reality tracking system that matches or exceeds the specifications of all competing systems. However, this system works only in 5 or 6-sided immersive display environment.

This project is the first step towards an adaptation of the technology for more general environments. In particular we target normal rooms and immersive displays with less than 5 screens. The technical work involves adapting the simulation software for the previous device to simulate a new design, and iteratively optimizing that design based on the results obtained.