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. 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