1 / 16

CK1 Intelligent Surface Modeler

CK1 Intelligent Surface Modeler. By Yu Wing TAI Kam Lun TANG Advised by Prof. Chi Keung TANG. Overview of presentation. Motivation Tensor Voting Algorithm Implementation Results Conclusion. Motivation Tensor Voting Algorithm Implementation Results Conclusion.

ondrea
Download Presentation

CK1 Intelligent Surface Modeler

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. CK1Intelligent Surface Modeler By Yu Wing TAI Kam Lun TANG Advised by Prof. Chi Keung TANG 2002-2003 FYP Presentataion

  2. Overview of presentation • Motivation • Tensor Voting Algorithm • Implementation • Results • Conclusion • Motivation • Tensor Voting Algorithm • Implementation • Results • Conclusion • theory and applications • tensor and voting • data representation and communication • bunny • dragon • etc Presented by: Yu Wing TAI Kam Lun TANG 2002-2003 FYP Presentataion

  3. Motivation • Theoretical interest • Emulate human visual perception • Applications • 3D modeling Presented by: Yu Wing TAI Kam Lun TANG 2002-2003 FYP Presentataion

  4. Overview of presentation • Motivation • Tensor Voting Algorithm • Implementation • Results • Conclusion Presented by: Yu Wing TAI Kam Lun TANG 2002-2003 FYP Presentataion

  5. What is Tensor Voting? • Representation • Constraint propagation • Data communication TENSOR VOTING FIELDS VOTING ALGORITHM Presented by: Yu Wing TAI Kam Lun TANG 2002-2003 FYP Presentataion

  6. + Tensor = Ellipse SMOOTH CURVE POINT JUNCTION = ELLIPSE (TENSOR) Presented by: Yu Wing TAI Kam Lun TANG 2002-2003 FYP Presentataion

  7. - stick tensor ball tensor 2D tensor Tensor = Ellipse - • Ball Tensor - 100% uncertainty in all directions • Stick Tensor - 100% certainty in normal directions Presented by: Yu Wing TAI Kam Lun TANG 2002-2003 FYP Presentataion

  8. 2D Stick Voting Field • Encode smoothness ? Presented by: Yu Wing TAI Kam Lun TANG 2002-2003 FYP Presentataion

  9. 2D Ball Voting Field • Derived from 2D stick voting field • Rotation and integration Presented by: Yu Wing TAI Kam Lun TANG 2002-2003 FYP Presentataion

  10. + = + = + = + = Voting Algorithm Each input site propagates its information in a neighborhood voting = summation of tensor votes accumulated in a neighborhood Presented by: Yu Wing TAI Kam Lun TANG 2002-2003 FYP Presentataion

  11. points curvels surfels Encode balls plates sticks Sparse Tensor Voting ball voting field plate voting field stick voting field tensor tokens dense tensor map Dense Tensor Voting surface saliency map surface Decompose Feature Extraction 3D Tensor Voting Presented by: Yu Wing TAI Kam Lun TANG 2002-2003 FYP Presentataion

  12. Results • Noisy data • Sparse data • Large scale reconstruction • Efficient neighborhood searching in 3D space • Code Optimization • Qualitative and quantitative analysis • Noisy data • Sparse data • Large scale reconstruction • Efficient neighborhood searching in 3D space • Code Optimization • Qualitative and quantitative analysis Presented by: Yu Wing TAI Kam Lun TANG 2002-2003 FYP Presentataion

  13. 100% noise 300% noise 500% noise 1000% noise 1500% noise 2000% noise 3000% noise 5000% noise Result: Robustness 2002-2003 FYP Presentataion

  14. Large scale reconstruction 1,153,856 triangles 35974 points Presented by: Yu Wing TAI Kam Lun TANG 2002-2003 FYP Presentataion

  15. Conclusion • Intelligent surface modeler • 3D surface description • Tensor voting • Results • Robustness • Large scale reconstruction • Future work • Multiscale feature segmentation and extraction Presented by: Yu Wing TAI Kam Lun TANG 2002-2003 FYP Presentataion

  16. Thank you Q&A 2002-2003 FYP Presentataion

More Related