1 resultado para VOLCANO CURVE
em Massachusetts Institute of Technology
Filtro por publicador
- Aberdeen University (3)
- Acceda, el repositorio institucional de la Universidad de Las Palmas de Gran Canaria. España (2)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (3)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (36)
- Aquatic Commons (7)
- Archimer: Archive de l'Institut francais de recherche pour l'exploitation de la mer (1)
- Archive of European Integration (1)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (3)
- Aston University Research Archive (11)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (5)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (11)
- Bioline International (1)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (39)
- Brock University, Canada (1)
- Bucknell University Digital Commons - Pensilvania - USA (1)
- Bulgarian Digital Mathematics Library at IMI-BAS (6)
- CaltechTHESIS (1)
- Cambridge University Engineering Department Publications Database (13)
- CentAUR: Central Archive University of Reading - UK (35)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (17)
- Collection Of Biostatistics Research Archive (1)
- Comissão Econômica para a América Latina e o Caribe (CEPAL) (2)
- CORA - Cork Open Research Archive - University College Cork - Ireland (2)
- DI-fusion - The institutional repository of Université Libre de Bruxelles (7)
- Digital Commons - Michigan Tech (17)
- Digital Commons - Montana Tech (1)
- Digital Commons at Florida International University (3)
- DigitalCommons@The Texas Medical Center (3)
- DigitalCommons@University of Nebraska - Lincoln (4)
- DRUM (Digital Repository at the University of Maryland) (1)
- eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry (2)
- Helda - Digital Repository of University of Helsinki (1)
- Indian Institute of Science - Bangalore - Índia (25)
- Instituto Politécnico de Viseu (1)
- Instituto Politécnico do Porto, Portugal (1)
- Massachusetts Institute of Technology (1)
- Ministerio de Cultura, Spain (1)
- Plymouth Marine Science Electronic Archive (PlyMSEA) (3)
- Publishing Network for Geoscientific & Environmental Data (284)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (38)
- Queensland University of Technology - ePrints Archive (242)
- Repositório digital da Fundação Getúlio Vargas - FGV (2)
- Repositório Institucional da Universidade Federal de São Paulo - UNIFESP (3)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (28)
- Repositorio Institucional Universidad EAFIT - Medelin - Colombia (1)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (1)
- Scientific Open-access Literature Archive and Repository (1)
- Universidad de Alicante (2)
- Universidad del Rosario, Colombia (1)
- Universidad Politécnica de Madrid (10)
- Universidade Complutense de Madrid (3)
- Universidade Federal do Pará (1)
- Universitat de Girona, Spain (1)
- Université de Lausanne, Switzerland (2)
- Université de Montréal, Canada (4)
- University of Michigan (21)
- University of Queensland eSpace - Australia (10)
- WestminsterResearch - UK (1)
Resumo:
Freehand sketching is both a natural and crucial part of design, yet is unsupported by current design automation software. We are working to combine the flexibility and ease of use of paper and pencil with the processing power of a computer to produce a design environment that feels as natural as paper, yet is considerably smarter. One of the most basic steps in accomplishing this is converting the original digitized pen strokes in the sketch into the intended geometric objects using feature point detection and approximation. We demonstrate how multiple sources of information can be combined for feature detection in strokes and apply this technique using two approaches to signal processing, one using simple average based thresholding and a second using scale space.