16 citations · 16 across the 1 of their papers we have counts for
4 papers
Real-Time Highly Accurate Dense Depth on a Power Budget using an FPGA-CPU Hybrid SoC
Oscar Rahnama, Tommaso Cavallari, Stuart Golodetz +5
Obtaining highly accurate depth from stereo images in real time has many applications across computer vision and robotics, but in some contexts, upper bounds on power consumption c…
Learning to Adapt for Stereo
Alessio Tonioni, Oscar Rahnama, Thomas Joy +3
Real world applications of stereo depth estimation require models that are robust to dynamic variations in the environment. Even though deep learning based stereo methods are succe…
RSGM: Real-time Raster-Respecting Semi-Global Matching for Power-Constrained Systems
Oscar Rahnama, Tommaso Cavallari, Stuart Golodetz +2
Stereo depth estimation is used for many computer vision applications. Though many popular methods strive solely for depth quality, for real-time mobile applications (e.g. prosthet…
Real-Time Dense Stereo Matching With ELAS on FPGA Accelerated Embedded Devices
Oscar Rahnama, Duncan Frost, Ondrej Miksik +1
For many applications in low-power real-time robotics, stereo cameras are the sensors of choice for depth perception as they are typically cheaper and more versatile than their act…