SDK CV Samples

The Computer Vision module provides algorithms that can be grouped into two categories:

• Signal processing algorithms used to transform the events stream (e.g. noise filters, ROI masks, transpose, rotation…)

• Signal analysis algorithms used to extract information from the events stream (e.g. counting events, frequency estimation, optical flow computation…)

In addition to those algorithms, the Computer Vision module also provides utility classes and functions useful in Computer Vision (e.g. camera models, non-linear solvers, etc).

Here is the list of samples provided with the CV module:

• Active Marker 2D Tracking Sample
• Data Rate Viewer using Python
• Data Rate Viewer using C++
• Sparse Optical Flow Sample using Python
• Sparse Optical Flow Sample using C++
• Dense Optical Flow Sample using Python
• Dense Optical Flow Sample using C++
• Noise Filtering using Python
• Noise Filtering using C++
• Undistortion Sample using C++
• XYT Tool