Robotics Service Bus

h1. Classifier Pipeline

h2. Structuring Ideas

* Data-flow layer + control layer
** E.g. central controller manages component states according to some protocol/rules

* Alternative: Subgraph lifecycles
** E.g. learning subgraph between data buffer and learner)

h2. Requirements

h3. Training

* Sequential processing: data source, keypoint, descriptor, feature
* Processing Strategies (in CCA speech)
** First possibility
*** As fast as possible
*** Flow control is necessary
*** Usually, all inputs are processed
** Second possibility
*** "Live" data source (i.e. camera)
* Multiple phases
** Collection
** Actual training
** Model is transmitted from learner to classifier

h3. h2. Classification

* Static, linear data flow: source, keypoint, descriptor, feature, classifier
* No buffering/persistence required

h2. Non-functional Requirements

* Parallel / distributed processing
* Visualization (when and what)
* Model description / specification (do skeletons exist?)

h2. Related work

* gstreamer
** usability is an issue
* IceWing
** data flow specification
** parallel processing (?)
** distributed processing (?)
** support for non-image data is not existent
** usability (?)
** no support for collection, training, classification phases / states