projects
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- | (Listed in order received.) | + | |
- | ====== Building an autonomous motorboat ====== | + | Currently offered Projects, Summer 2013 |
- | **Supervisor**: | + | (some projects still subject to confirmation) |
- | **Required Background**: | ||
- | **Recommended Background**: | + | ====== 3D Drawing System with Leap Motion finger tracker ====== |
- | __Description__ | + | **Supervisor**: |
- | An opportunity exists for a small number of students to build an autonomous motorboat using a RC motorboat as a base and integrating computation and control in the form of a Beagleboard. Students will participate in lectures and labs associated with CSE6324 (Part I). Interested students should attend the first lecture of CSE6324. See the departmental schedule for time and place. | + | |
+ | **Required Background**: | ||
+ | The Leap Motion, leapmotion.com, | ||
- | ---- | + | ====== 3D Drawing System with 3Gear gesture tracker ====== |
- | : | + | |
- | ---- | + | |
- | ====== Athenians Data Project ====== | + | **Supervisor**: |
- | **Supervisor**: Nick Cercone | + | **Required Background**: 3D computer graphics, C/C++ coding |
- | **Required Background**: | + | The 3Gear system, threegear.com, |
- | **Recommended Background**: | ||
- | __Description__ | ||
- | The Athenians Project is a multi-year, ongoing project of compiling, computerizing and studying data about the persons of ancient Athens. | ||
- | Possible project ideas for this term span from simpler ones such as | ||
- | how to present data in the best possible way, add spatial characteristics to existing data, | ||
- | add multimedia data, improve text searching, etc. to more complex ideas such as filling | ||
- | missing parts for the " | ||
- | words has been done in the past using expert knowledge. Those experts have establish | ||
- | certain rules/ | ||
- | when talking in IT terminology. Furthermore, | ||
- | the database with some likelihood. Associating probabilities with hypotheses introduces | ||
- | another opportunity for research projects. | ||
- | ---- | ||
- | : | ||
- | ---- | ||
- | ====== | + | ====== |
- | **Supervisor**: | + | **Supervisor**: |
- | **Requirements**: | + | **Required Background**: General 4080 prerequisites, |
- | __Description__ | + | Touchscreen mobile devices commonly use a built-in accelerometer to sense movement or tilting actions of the device. |
- | To provide visual surveillance over a large environment, many surveillance cameras are typically deployed at widely dispersed locations. | + | **Readings**: |
- | This problem can be addressed by automatically pre-mapping two-dimensional surveillance video data into three-dimensional coordinates. | + | ====== Attentive Sensing for Better Two-Way Communication |
- | Mapping surveillance video to three-dimensional coordinates requires construction of a virtual model of the three-dimensional scene. | + | **Supervisor**: |
- | This project will investigate a monocular method for inferring three-dimensional context for video surveillance. | + | **Required Background**: |
+ | good math skills, knowledge | ||
- | Although | + | One of the challenges in remote learning is to allow students to communicate effectively with the lecturer. |
+ | |||
+ | The goal of this project | ||
+ | |||
+ | In particular, working with a senior graduate student or postdoctoral fellow, the successful applicant will: | ||
+ | |||
+ | | ||
+ | - Implement algorithms for detecting hand-raises based upon this investigation | ||
+ | | ||
+ | |||
- | 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. | + | ====== Continuation |
- | For more information on the laboratory: [[http:// | + | **Supervisor**: Jeff Edmonds |
- | ---- | + | **Required Background**: General CSE408x prerequisites |
- | : | + | |
- | ---- | + | |
- | ====== Estimating Pedestrian and Vehicle Flows from Surveillance Video ====== | + | **Recommended Background**: |
- | **Supervisor**: | + | Structural equation modeling (SEM) is a statistical technique that is becoming increasingly popular in the educational and behavioral sciences. SEM allows researchers to test the validity of hypothesized models involving complex relationships among multiple variables. Collected data is used to estimate the parameters of the equations and assessing the fit of the model. |
- | **Requirements**: | + | The software required is an application that allows researchers to define their hypothesized models visually and will output the correct syntax for the analytical software of their choosing. |
- | __Description__ | + | To date a promising functional application has been developed in JAVA by a Computer Science student as a 4080 project. The existing software allows the user to draw a path diagram and outputs code for the R package sem. There are a number of improvements to be made (refinements and additions to graphical user interface) and then the application needs to be extended to output syntax appropriate for additional software applications (openMX, MPlus and EQS). Though this project may not begin at “the first stages” of the software lifecycle, this scenario is likely common in the software development market. In addition, the student will be working with a primary “client” who is far less technically advanced, which is also reflective of real-world situations. |
- | 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. | + | More details {{: |
- | The density of permanent urban video surveillance camera installations has increased dramatically over the last several years. | ||
- | 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. | + | ====== Numerical Methods ====== |
- | For more information on the laboratory: [[http:// | + | **Supervisor**: Mike McNamee |
- | + | ||
- | ---- | + | |
- | : | + | |
- | ---- | + | |
- | ====== Tandem repeat detection using spectral methods ====== | + | **Required Background**: |
+ | of Fortran, C or similar language. | ||
- | **Supervisor**: Suprakash Datta | + | **Description**: Write, debug and run several Fortran programs related to solving |
+ | polynomial equations, with a view to comparing different known methods. | ||
- | **Required Background**: | + | ====== Enabling SaaS access to an experimental AI planner ====== |
- | **Recommended Background**: Some background in Statistics is desirable but not essential. | + | **Supervisor**: Sotirios Liaskos (liaskos at yorku dot ca) |
- | __Description__ | + | **Required Background**: |
- | DNA sequences | + | 3402 -- Functional & Logic Programming, |
+ | 3101 -- Design | ||
+ | 4302 -- Compilers and Interpreters. | ||
- | Finding tandem repeats is an important problem in Computational Biology. The techniques that have been proposed for it fall into two classes: string matching algorithms and signal processing techniques. In this project, we will explore fast, accurate algorithms for detecting tandem repeats | + | **Description**: This project |
- | The student will implement existing spectral algorithms based on Fourier Transforms | + | The components are various Unix executables |
+ | Learning objectives: | ||
+ | * Understand the technologies and process involved in turning native code into a web-service (" | ||
+ | * Study a state-of-the-art AI planner and understand its workings. | ||
+ | * Exercise scripting skills. | ||
+ | ====== Predicting Angular Error in Rigid Registration ====== | ||
- | ---- | + | **Supervisor**: Burton Ma |
- | : | + | |
- | ---- | + | |
- | ====== Touch- and Gesture-based Text Entry With Automatic Error Correction ====== | + | **Description**: |
+ | navigation. Several (seemingly) different approaches for predicting | ||
+ | distance errors in registration are known, but for some surgical | ||
+ | procedures, the angular error in registration is more important. | ||
+ | This project will validate an approach for predicting angular | ||
+ | error in registration; | ||
+ | simulated | ||
- | **Supervisor**: | + | ====== Calibration of a Tracked Pointer ====== |
- | **Required Background**: | + | **Supervisor**: Burton Ma |
- | CSE3461 (or equivalent), | + | |
- | A student wishing to do this project must be well versed in Java, Eclipse, and developing java code for the Android operating system. | + | |
+ | **Description**: | ||
+ | navigation systems. A typical pointer has a tracked target on one | ||
+ | end and a sharp or ball tip on the other end. Finding the location | ||
+ | of the tip relative to the target is a calibration problem. One | ||
+ | solution to the calibration problem involves pivoting the pointer | ||
+ | about the tip while tracking the target; if the tip is kept | ||
+ | stationary, then the target moves on the surface of a sphere. | ||
+ | Fitting the tracking data to the surface of a sphere yields the | ||
+ | location of the tip as the sphere center. Unfortunately, | ||
+ | calibrated tip position obtained using such a spherical calibration | ||
+ | has high variance. This project will investigate how much variance | ||
+ | there is in the calibrated tip position, and methods for reducing | ||
+ | the variance of the calibrated tip position. | ||
- | **Recommended Background**: | ||
- | Possession of an Android touch-based phone or tablet would be an asset, but is not essential. | ||
- | __Description__ | + | ====== A privacy safeguard framework for sharing photos |
- | This project involves extending a touch-based text entry method to include automatic error correction. | + | |
+ | **Supervisor**: | ||
+ | |||
+ | **Description**: | ||
+ | One of the major privacy concerns in Online Social Networks is photo sharing. | ||
- | ---- | + | **Required |
- | : | + | |
- | ---- | + | |
- | ====== Early Breast Cancer Detection based on MRI’s. ====== | + | |
- | + | ||
- | **Supervisor**: | + | |
- | + | ||
- | **Required | + | |
- | + | ||
- | **Recommended | + | |
- | + | ||
- | Project Description: | + | |
- | processing techniques for early detection of breast cancer using the available | + | |
- | modalities. In particular, we propose to develop time reversal beamforming imager, | + | |
- | based on our earlier work in time reversal signal processing, for detecting early stage | + | |
- | breast cancer tumours from MRI data. | + | |
- | Our preliminary work has illustrated the type of | + | |
- | results that are possible for breast cancer detection by applying time reversal signal | + | |
- | processing on MRI breast data. In this research, we propose to extend these results to | + | |
- | provide a quantitative understanding of the practical gains provided by time reversal | + | |
- | in MRI based breast cancer detection and its limitations. This will be accomplished | + | |
- | a local hospital, | + | |
- | important to check the validity of our algorithms. The next step is to compare the | + | |
- | estimated locations of the tumours (as derived with our algorithms) to their precise | + | |
- | locations as identified by the pathologists. The second step will quantify the accuracy | + | |
- | of our estimation algorithms. | + | |
- | ---- | + | **Desired prerequisite**: Knowledge of image processing, Facebook API, JavaScript Object Notation (JSON) |
- | : | + | |
- | ---- | + |
projects.txt · Last modified: 2016/01/13 20:05 by stevenc