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Zhigang Zhu Visual Computing Laboratory Department of Computer Science

C. C V C L. Pervasive Computing Experience in Planning a Center for P erceptual R obotics, I ntelligent S ensors & M achines. Zhigang Zhu Visual Computing Laboratory Department of Computer Science City College of the City University New York

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Zhigang Zhu Visual Computing Laboratory Department of Computer Science

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  1. C CVC L Pervasive Computing Experience in Planninga Center forPerceptual Robotics, Intelligent Sensors & Machines Zhigang Zhu Visual Computing Laboratory Department of Computer Science City College of the City University New York http://www-cs. ccny.cuny.edu/~zhu/ John (Jizhong) Xiao Robotics and Intelligent Systems Lab Department of Electrical Engineering City College of the City University New York Website: http://134.74.16.73

  2. Outline • Problems and Our Goal • Vision/Robotics Research • The planned PRISM Center • MVC: Multimedia Virtualized Classroom • Automatic multimedia capture (Audio, video, text…) • Intelligent media integration and indexing • User-customized presentation • RISE-NET: Robotized Intelligent Sensor Networks • Stereo mosaics: Airborne, ground & under-vehicle inspection • Wall-climbing robots /smart miniature robots • Summary Pervasive Computing

  3. Outline • Problems and Our Goal • Vision/Robotics Research • The planned PRISM Center • MVC: Multimedia Virtualized Classroom • Automatic multimedia capture (Audio, video, text…) • Intelligent media integration and indexing • User-customized presentation • RISE-NET: Robotized Intelligent Sensor Networks • Stereo mosaics: Airborne, ground & under-vehicle inspection • Wall-climbing robots /smart miniature robots • Summary Pervasive Computing

  4. IntroductionCCNY & PRISM Pervasive Computing

  5. CUNY System w/ Vision and Robotics CUNY City College Graduate Center Brooklyn Hunter Queens … Flagship campus HSI / MI (PhD granting institution*) SOE * Site of PhD programs in Engineering ME CS EE PRISM Center Planned Center for Perceptual Robotics, Intelligent Sensors and Machines under NSF MII planning program Pervasive Computing

  6. Vision & Robotics People at CCNY • Prof. Izidor Gertner • Image processing, data fusion, parallel processing • Prof. Michael Grossberg • Physics-based vision, machine learning • Prof. Esther Levin • Spoken language HCI, machine learning • Prof. Jie Wei • Vision, Multimedia Digital Library • Prof. George Wolberg • Vision, graphics • Prof. Jizhong (John) Xiao • Robotics, control • Prof. Zhigang Zhu • Vision, video computing, robotics, HCI Pervasive Computing

  7. PRISM: a Center for Vision and Robotics • NSF Planning Project (Grant No. CNS-0424593) • Planning a CCNY PRISM Center • PIs: Jizhong Xiao, Zhigang Zhu • Research Center of Excellence in • Distributed Perceptual Robotics (RISE-NET) • Intelligent Sensors (MM) • Smart Machines (HCI) • Education Environment • For PhD, MS, undergrad and high school students • Serving underrepresented students • CCNY- MI and HSI Pervasive Computing

  8. PRISM: a Center for Vision and Robotics • Infrastructure in Place or in Plan • Airborne and Indoor/Outdoor Mobile Platforms • UAVs, outdoor robots, indoor robots • Heterogeneous Sensor Packages (AFRL) • Miniature and high-end cameras, acoustic, LDV • GPS, INS , ladars, online processors • Fast Prototyping Machine (ARO) • For fabricating wall-climbing robots • Various Levels of Vision Processors (NSF MRI) • Compact, high-end, low-cost, low power • Wireless Sensor Networks (CCNY Samsung Lab) • Practical for imaging sensors and robots Pervasive Computing

  9. Outline • Problems and Our Goal • Vision/Robotics Research • The planned PRISM Center • MVC: Multimedia Virtualized Classroom • Automatic multimedia capture (Audio, video, text…) • Intelligent media integration and indexing • User-customized presentation • RISE-NET: Robotized Intelligent Sensor Networks • Stereo mosaics: Airborne, ground & under-vehicle inspection • Wall-climbing robots /smart miniature robots • Summary Pervasive Computing

  10. Multimedia Integration for a Virtualized Classroom • Collaborators • Rick Adrion, Ed Riseman, Al Hanson, Jim Kurose, (UMass) • Parviz Kermani, IBM / PINY • Student: Weihong Li, Hao Tang, Chad McKittrick • Supported by • CUNY CISDD, NSF EIA (UMass) Pervasive Computing

  11. Multimedia Virtualized Classroom • Goal: automating e-learning in MVC • Automatic capture (A, V, WB, BB) • Intelligent media integration • User-customized presentation • Problem and Promise • Joint proposals with UMass to NSF • MVC is a smart room, part of the effort in building a PRISM center for research and learning • Many good examples of advance MM classrooms • Georgia Tech, UIUC, UMass, … Pervasive Computing

  12. conversion index PPT Capture Add-on registration Mimio Virtual Ink video transformation Remote Reality Omnidirectional Camera MVC: Automatic MM capture Pervasive Computing

  13. video PPT slides Handwriting pages S V1 H V2 combined MVC: Media Integration

  14. MVC: Media Integration Panoramic mosaic from video Pervasive Computing

  15. MVC: Media Integration Panoramic mosaic from video Pervasive Computing

  16. Active WWW link Synthetic Hi-Res digital display Slide combined with video Panoramic mosaic from video Annotated and active instructor MVC: Media Integration Toward an immersive VC interface Question Window, ToC, etc Pervasive Computing

  17. MVC: Media Integration Instructor Extraction…and integration video image shadow contour Pervasive Computing

  18. User Customized Presentation • Virtualized Classroom Presentation System (VCPS) in Java, consists of • An authoring tool –VCPS creator • An presentation interface - VCPS player • Features • Customized sizes and locations • Pop up ToC for indexing • Synchronized play, next, last… Pervasive Computing

  19. User Customized Presentation • PPT+ panoramic view + popup ToC Pervasive Computing

  20. User Customized Presentation • PPT+ Mimio + Combined + images +New Buttons Pervasive Computing

  21. Outline • Problems and Our Goal • Vision/Robotics Research • The planned PRISM Center • MVC: Multimedia Virtualized Classroom • Automatic multimedia capture (Audio, video, text…) • Intelligent media integration and indexing • User-customized presentation • RISE-NET: Robotized Intelligent Sensor Networks • Stereo mosaics: Airborne, ground & under-vehicle inspection • Wall-climbing robots /smart miniature robots • Summary Pervasive Computing

  22. RISE-NET: Robotized Intelligent Sensor Network in 3Dfor surveillance and security • Joint Work with • George Wolberg, John Xiao @ CCNY • Bob Haralick @ CUNY Graduate Center • Ed Riseman, Al Hanson, Rod Grupen @ UMass • Tom Huang @ UIUC • Supported by NSF, DARPA,AFRL, ARO, NYSIA, ACTI, etc Pervasive Computing

  23. Goal • Dream: • transform the present 2-D world of mobile rovers into a new 3-D universe –air, ground, under-object, and wall-climbing • move on ground, climb walls, walk on ceilings, transit between surfaces. • Applications: • Urban warfare applications: surveillance and reconnaissance, weapon delivery, guiding perimeter around a building, etc • Security and counter-terrorist applications: intelligence gathering about a hostile situation within a building, etc. • Inspection and maintenance applications: routine inspection of buildings, nuclear containment domes, and other hard-to-reach places, inspection of aircraft, sand blasting of ship hulls, etc. • Other Civilian applications: assistance in firefighting, search and rescue operations, etc. Pervasive Computing

  24. Some Real Examples • City/Urban modeling (NSF/AFRL/NYSIA) - airborne video: far-view (1000 ft) • Robot Navigation (DARPA, ARO)- ground video: medium range (~100ft) • Facade inspection (ARO) – climbing robots: near-view (inches?) • Under-vehicle inspection (ACTI) - car drives over camera: near-view (< 8 in) Pervasive Computing

  25. Objectives • Input: 2D array of cameras • multiple viewpoints; motion parallax • Output: Content-based representation • WFOV, Stereo, Occlusion Rep. -> 3D and Moving targets Pervasive Computing

  26. Airborne Stereo Mosaics:What is the Goal? • Joint Work with • George Wolberg, Robert Haralick, Hao Tang (CUNY) • Allen Hanson, Edward Riseman (UMass) • Dr. Jeff Layne (AFRL) • Supported byAFRL, NSF and NYSIA • Publications: ICCV01, VideoReg03, PAMI04, A3DISS05 Pervasive Computing

  27. Objectives • Rapidly create large FOV image mosaics that are • geo-referenced, • with 3D (stereo) viewing and • with all moving targets identified • could be dynamically updated • As a light UAV flights over an area Pervasive Computing

  28. Objectives • Rapidly create large FOV image mosaics that are • geo-referenced, • with 3D (stereo) viewing and • with all dynamic targets identified • As a light UAV flights over an area Pervasive Computing

  29. Region-Based Stereo Matching Left mosaic – Full Depth Map Pervasive Computing

  30. Region-Based Stereo Matching • under development… Left mosaic – closeup Pervasive Computing

  31. Region-Based Stereo Matching • under development… Left mosaic – Depth and Motion Pervasive Computing

  32. Objectives • Rapidly create large FOV image mosaics that are • geo-referenced, • with 3D (stereo) viewing and • with all dynamic targets identified • As a light UAV flights over an area Pervasive Computing

  33. Ground 3D Panoramas:autonomous vehicle navigation • Joint Work with • Allen Hanson, Edward Riseman (UMass) • Roderic Grupen (UMass) • Supported by DARPA • Publications : CVPR99, ICCV01, CVIU04, IJCV05 Pervasive Computing

  34. An Indoor Example • Video under translation • Varying depths • Wide FOV stereo mosaics and • Mosaic-based virtual walk-through Pervasive Computing

  35. Under-Vehicle Stereo Mosaics:3D vehicle inspection • Joint Work with • Allen Hanson, Edward Riseman,Howard Schultz(UMass) • P. Dickson, J. Li (UMass), Gary Whitten ( ACTI) • Supported by ACT • Publications : WACV02, AIPR03, ICIP05 Pervasive Computing

  36. Camera Geometry • Car drives over a 1D array of cameras… Pervasive Computing

  37. One camera to N stereo mosaics • Very near range view • Distortion removal • Motion estimation • Stereo mosaicing • anomaly detection Pervasive Computing

  38. UVIS: Dynamic Stereo Mosaics Anti-Terrorism: Under-Vehicle Inspection 5 mosaics with changing viewing directions Stereo mosaics: Each pair of 5 mosaics is a stereo pair Dynamic mosaics: Look around objects even without stereo Pervasive Computing

  39. UVIS: Dynamic Stereo Mosaics Anti-Terrorism: Under-Vehicle Inspection 5 mosaics with changing viewing directions Stereo mosaics: Each pair of 5 mosaics is a stereo pair Dynamic mosaics: Look around objects even without stereo Pervasive Computing

  40. UVIS: Dynamic Stereo Mosaics Anti-Terrorism: Under-Vehicle Inspection 5 mosaics with changing viewing directions Stereo mosaics: Each pair of 5 mosaics is a stereo pair Dynamic mosaics: Look around objects even without stereo Pervasive Computing

  41. UVIS: Dynamic Stereo Mosaics Anti-Terrorism: Under-Vehicle Inspection 5 mosaics with changing viewing directions Stereo mosaics: Each pair of 5 mosaics is a stereo pair Dynamic mosaics: Look around objects even without stereo Pervasive Computing

  42. UVIS: Dynamic Stereo Mosaics Anti-Terrorism: Under-Vehicle Inspection 5 mosaics with changing viewing directions Stereo mosaics: Each pair of 5 mosaics is a stereo pair Dynamic mosaics: Look around objects even without stereo Pervasive Computing

  43. Sensor Network in 3Dfor wall-climbing robots • Joint Work with • John Xiao (EE @ CCNY), Ali Sadegh (ME @ CCNY) • Yi Feng (GC @ CUNY) • Supported by NSF, ARO • Related Publications: OmniVision00, CVIU04, RAM04 Pervasive Computing

  44. Existing Technologies and Robots CMU gecko inspired climber • Existing wall-climbers: JPL-Stanford rock climber MSU “Flipper” & “Crawler” Avionic Instruments Inc. Vortex attraction technique iRobot’s Mecho-Gecko Pervasive Computing

  45. Wall Climber: Adhesive Mechanism • Design alternatives: • vacuum pumps (MSU climber) • vortex attraction device • vacuum rotor package Pervasive Computing

  46. Wall Climber: Vacuum Chamber Seal • Inflated Tube Skirt Seal • Flexible Bristle Skirt Seal attraction force is so strong that it anchored the device to wall surfaces trade-off between sealing and mobility Pervasive Computing

  47. Wall Climber: Selected Design • Selected Design • vacuum rotor package • flexible bristle skirt seal • differential drive • pressure force isolation rim (re-foam) • improves mobility, & enhances sealing by reducing the deformation of the skirt Pervasive Computing

  48. Wall Climber: Transition Mechanism • Transition Mechanism • Modular Design Four wall-climber modules are configured to form a larger wall-climbing robot which can carry heavy payload Pervasive Computing

  49. Vision for Cooperative Climbing Robots • View planning in 3D • with robots on ground, walls and ceilings • Scene and object understanding • to recognize floor, walls, obstacles, ceilings • by taking advantage the climbing feature of multiple wall-climbers in 3-D environments Pervasive Computing

  50. Robot Localization and View Planning • Mutual awareness • Heterogeneous sensors • Active Sensing • Robust Features • for tracking and matching • SIFT Pervasive Computing

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