Post

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: 1. Ground-truth available datasets 2. Evaluate current attentive algorithms on these datasets 3. Modify these algorithms to improve performance on these datasets