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RP3 Middleware & TennisSense

RP3 Middleware & TennisSense. Gregory O’Hare, Richard Tynan, Conor Muldoon & Anthony Schoofs. TennisSense Overview. Application Goals: 1. Sense tennis player 2. Assist tennis coach/player to improve their game Technical Goals: 1. Correlate multiple sensory data sources

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RP3 Middleware & TennisSense

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  1. RP3 Middleware & TennisSense Gregory O’Hare, Richard Tynan, Conor Muldoon & Anthony Schoofs

  2. TennisSense Overview Application Goals: 1. Sense tennis player 2. Assist tennis coach/player to improve their game Technical Goals: 1. Correlate multiple sensory data sources 2. Automated analysis of sensory data 3. Delivery of data to the coach/player

  3. Initial Configuration Ubisense x 4 Foster-Miller x 4 Inertial x 100(approx) ? XML Annotation Camera x 9 Player zone Player location ... Image Analysis Player location Ball location Rally Start ... Query: Is player serving?

  4. Why Use Middleware? Enhances interoperability between systems Facilitates data management – e.g. fusion/correlation Future Applications Flexibility – adapt to new parts of the application automatically Reuse – automatically reuse application components Data structure and data semantics can be encoded

  5. Proposed Configuration Ubisense x 4 Foster-Miller x 4 Inertial x 100(approx) Camera x 9 Multi-Agent System Middleware Image Analysis Image Analysis XML Annotation PZT Camera Control XML Annotation QoS Metric: how often is player in frame? Query: Is player serving?

  6. Pros and Cons Abstraction to data sources, controllers and actuators Consistent and homogenous communication protocol ACL – FIPA compliant messages Real time decision making Facilitates addition of new sub-applications Agent migration can effectively balance load May possibly slow down analysis

  7. Proposed Scenario Base Line Rally Detection 1. Sense player and ball data 2. Identify signatures in data e.g. base line rally 3. PZT control of cameras QoS – optimise duration player is in shot Agents may refine standard PZT values for the cameras based on a QoS feedback loop

  8. Completed Tasks 4 files Richie – Ubisense data -> agent beliefs Anthony – 3 camera files -> agent beliefs Using intermediate/indirect file based approach not appropriate Awaiting feedback from DCU on the proposed scenario Transitioning to using live data rather than logs

  9. Current Configuration Ubisense x 4 Foster-Miller x 4 Inertial x 100(approx) ? XML Annotation Camera x 9 Player zone Player location ... Image Analysis BEL(playerZone(5)) BEL(playerLocation(7, 10)) … Player location Ball location Rally Start ... Query: Is player serving?

  10. Goal: PTZ Camera Control Full Picture Set pan, tilt and zoom to ensure player is in frame Some cameras virtually pan and tilt Some cameras will physically pan and tilt Achieved through data integration

  11. Agent Software Ubisense data indicates the player’s coordinates - (x(t), y(t), z(t)) Perceptor takes live data feed of player’s location Beliefs are created e.g. BEL(playerLocation(x, y, z)) Actions can be triggered according to the agent’s desires For example, controlling PZT camera values to ensure player is in shot

  12. PTZ Calculation

  13. Camera Control Agent actuator invokes the http API of the networked video camera Example: http://camera/ptz.cgi? parameter=value Absolute positioning: http://camera/ptz.cgi?pan=20&tilt=-10&zoom=900 Alternative with areazoom: http://camera/ptz.cgi?areazoom=30,40,300 Can also perform relative positioning with a URL

  14. Current Configuration 2 Ubisense x 4 BEL(playerLocation(7, 10)) … Camera x 9

  15. Remaining Tasks 1a. Middleware closer to sensors 1b. Viability - in network processing/real time experiments 2. Video analysis to automatically determine % of time player is covered by camera 3. Close the loop – provide the control/feedback loop for cameras and ubisense data 4. Live Testing

  16. This is a slide title • This is a first level heading • And this is a second level heading • Here is another first level heading • Followed by another second level • And one more level 1 • And a final second level • So these slides are good for about 4 main bullets • And some detail text per slide

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  18. Half-way down the Vallee Blanche Note the blue glacial ice! Neat eh?

  19. A right hand picture slide • Emerald Bay, Lake Tahoe • The most amazing place! • Level 1 heading • Level 2 heading • Level 1 heading • Level 2 heading • Level 1 heading • Level 2 heading

  20. A right hand chart slide • Level 1 heading • Level 2 heading • Level 1 heading • Level 2 heading • Level 1 heading • Level 2 heading • Level 1 heading • Level 2 heading

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