Up: Mark D. Wheeler: Research Previous: Current Research

Future Plans

In the future, I plan to extend the probabilistic recognition paradigm to use contextual indicators (e.g., the environmental conditions) and goals to drive the prior probabilities (i.e., using expectation to improve efficiency). I believe this direction of research is a key to achieving efficient recognition over a wide range of scenarios with large model bases. My thesis research only considers rigid objects (i.e., 6 degrees of freedom). Extending the techniques to apply to articulated objects such as human forms is another line of research I plan to pursue. I am familiar with machine learning and neural networks and am interested in exploring the use of techniques from these fields to aid or enhance solutions to computer vision problems. Recently, the graphics and vision communities have demonstrated simple techniques that process visual data to produce astonishing graphical effects (e.g., image mosaicing and morphing). The door is open for applications of computer vision techniques to automate these effects, and I am very anxious to collaborate with graphics researchers on these problems.

Mark Wheeler