Research
My long term research goal is visual understanding through extended robotic interactions with the world. Broad themes of my work include object segmentation and recognition, perceptual organization, visual collision detection, inertial aiding for vision, visual navigation and real time embedded video processing.
Recent projects have focused on computer vision for unmanned air vehicles (UAVs):
- VAMAV: Visual obstacle detection and avoidance for a micro air vehicle using expansion segmentation for time to collision estimates.
- VISTA: Stereo based obstacle detection for small UAVs.
- SAFESEE: EO/IR/LIDAR sense and avoid for unmanned air vehicles
- ImageNav: Image aided navigation for an unmanned air vehicle in GPS denied areas.
- EVASE: Supervised learning and 2D pattern classification in noisy video.
- K-cut Image Segmentation: Perceptual organization using multiway graph cuts.
- Constrained Fuzzy Clustering: Constrained fuzzy clustering for target detection in particle filters.
Completed projects at the Carnegie Mellon University Robotics Institute (CMU-RI):
- Reconfigurable Vision Machine: Research staff for modular architecture and software tools for high performance machine vision.
- Micro Vision Engine: Consultant on low noise analog NTSC layout for a vision computer suitable for a small unmanned vehicle.
- TUGV: Research assistant on high speed cross country navigation using stereo vision for the Transitional Unmanned Ground Vehicle.
- Virtualized Reality: Research assistant on hardware and software based camera synchronization for multibaseline 3D reconstruction.
- Automated Timber Inventory: Precise texture segmentation for tree diameter estimation.
