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# Guess the Depth PowerPoint PPT Presentation

REMINGTON GONG BENJAMIN HARRIS IURI PRILEPOV. Guess the Depth. WHAT WE HAVE DONE. Created a profiler to sample current performance of feature tracking Useful for deciding which of next stages are worth implementing on GPU Started the eight-point algorithm implementation

Guess the Depth

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REMINGTON GONG

BENJAMIN HARRIS

IURI PRILEPOV

## Guess the Depth

### WHAT WE HAVE DONE...

• Created a profiler to sample current performance of feature tracking

• Useful for deciding which of next stages are worth implementing on GPU

• Started the eight-point algorithm implementation

• Researched SVD-based methods for recovering rotation and translation between correspondence pairs

### FEATURE TRACKING PERFORMANCE

• Setup:

• Video - 640x320 @ 24Hz

• Laptop - Intel Core 2 T7500, NVIDIA 8600M GT

Note: Average times do not sum to total average time since some phases (i.e. new feature selection) are not always computed.

### Performance Observations

• Feature tracking on GPU is fast, but GPU memory copy-back during feature selection hurts (5 ms)

• Convolution is expensive on GPU due to numerous texture fetches despite trivial parallelism

• Lots of room for improvement, but currently capable of 35Hz

• Several stages still to be implemented

### Eight-Point Algorithm

• Recover 3D coordinates from a set of point correspondences between two frames

• Least-squares approximation of the Essential Matrix (camera movement)

• SVD – Jama linear algebra package

• Normalization of input coordinates