Optical Flow Sample¶
The Computer Vision API can be used to compute the optical flow of objects moving in front of the camera. The optical flow is computed in a sparse way: flow information is generated on clusters of events and not for each event.
The sample in
shows how to implement a pipeline for computing the sparse optical flow.
The sample visualizes events and the output optical flow with arrows indicating direction and magnitude of motion:
The sample also generates a video with the output flow.
How to start¶
First, compile the sample as described in this tutorial.
To start the sample, you need to provide recorded data with the full path to a RAW file (here, we use the file from Metavision Dataset):
Metavision Optical Flow sample implements the following pipeline:
Spatio Temporal Contrast Filter Stage¶
This stage applies the
Metavision::SpatioTemporalContrastAlgorithmT to reduce the noise in the events
The filtered events are then sent to both the optical flow and frame generation stages.
Sparse Optical Flow Stage¶
This stage applies the
Metavision::SparseOpticalFlowAlgorithm on the events stream and produces
Metavision::EventOpticalFlow events for each internally detected events cluster. Events are clustered
together based on their speed and directions: events with a similar speed and direction are clustered and flow is
computed for them.
Frame Generation Stage¶
This stage uses the
Metavision::FlowFrameGeneratorAlgorithm to generate a frame that will be used later on
in the display stage to visualize the result of the
Metavision::SparseOpticalFlowAlgorithm by rendering the
estimated flows on the top of the events.
As shown in the graph, the optical flow events and the CD events are received in parallel meaning that the optical flow
events and CD events have to be synchronized in some ways. This is done in the
Metavision::FlowFrameGenerationStage by buffering the incoming events and producing the image when
Different approaches could be considered for more advanced applications.
Metavision::FlowFrameGenerationStage class, the methods
Metavision::BaseStage::set_previous_flow_stage() allow to redirect the input data to the corresponding
When ready, the output frame is sent to the display stage.
This stage allows us to visualize the previously generated image on the screen: