Background Subtraction

Algorithms seperating the input point cloud into foreground and background.

Table 1. Available fields in blickfeld.percept_pipeline.config.BackgroundSubtraction
Field	Type	Default	Unit
mixture_of_gaussians	MixtureOfGaussians	-	-
mixture_of_gaussians	Use mixture of gaussians for foreground/background detection
octree	Octree	-	-
octree	Use a static octree for foreground/background detection.

Mixture Of Gaussians

Dynamic background subtraction using a mixture of gaussians. The algorithm automatically slowly updates the background model if the scene changes. The update rate is controlled via 'exponential_decay'.

Table 2. Available fields in blickfeld.percept_pipeline.config.BackgroundSubtraction.MixtureOfGaussians
Field	Type	Default	Unit
num_initialization_frames	uint32	-	-
num_initialization_frames	How many frames of the first received frames are used to build the background Reasonable default: 10
exponential_decay	float	-	-
exponential_decay	Controls how fast objects switch between foreground and background. Exponential decay factor. Reasonable default: 0.005
min_weight_threshold_for_background	float	-	-
min_weight_threshold_for_background	Controls how much noise the background/foreground is expected to have. Reasonable default: 0.25

Octree

Uses the first received frames to build a static background map of the environment. The algorithm requires the scene to only contain the static parts of the scene on the start of the processing. The background model is not updated automatically afterwards. The ResetBackground grpc method allows to update the static map of the environment.

Table 3. Available fields in blickfeld.percept_pipeline.config.BackgroundSubtraction.Octree
Field	Type	Default	Unit
num_initialization_frames	uint32	-	-
num_initialization_frames	How many frames of the first received frames are used to build the background Reasonable default: 10