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--- projects [2013/04/19 20:28] – mb
+++ projects [2013/04/23 16:10] – mb
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   - Implement algorithms for detecting hand-raises based upon this investigation
   - Evaluate these algorithms in a real-classroom setting, using proprietary attentive sensing technology
+====== Attentive Sensing for Sport Video Recording Markets ======
+**Supervisor**: James Elder
+**Required Background**: Good programming skills; Good math skills; Knowledge of C and MATLAB programming languages
+The goal of this project is to modify York University’s patented attentive sensor technology to the sport video recording market.  Specific application domains under investigation include skiing, indoor BMX parks, and horse tracks.
+The general problem is to use attentive sensing technology (www.elderlab.yorku.ca) to visually detect and track multiple moving agents (e.g., skiers, riders, horses) and to select specific agents for active high-resolution smooth pursuit.
+The student will work with senior graduate students, postdoctoral fellows and research scientists to help modify the attentive sensing technology to operate in these domains.   Specific tasks include:
+.     Ground-truth available datasets
+.     Evaluate current attentive algorithms on these datasets
+.     Modify these algorithms to improve performance on these datasets
@@ Line 69: / Line 89: @@
-====== Numerical Methods ======
-**Supervisor**: Mike McNamee
-**Required Background**: Good grade in a Numerical Methods course and good knowledge
-of Fortran, C or similar language.
-**Description**: Write, debug and run several Fortran programs related to solving
-polynomial equations, with a view to comparing different known methods.
 ====== Enabling SaaS access to an experimental AI planner ======