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Enhancing Image Annotation and Hand Detection Systems: Insights from Week 2 Presentations

This presentation recaps key topics from Week 2 of the REU program. It highlights the importance of image annotation systems, emphasizing the gap between low-level features and high-level semantic queries. Notable papers include a review of image annotation systems and their applications in content-based image retrieval (CBIR). Additionally, the research on hand detection techniques, specifically recognizing American Sign Language letters through Principal Component Analysis, is discussed. Ongoing projects will continue to focus on hand detection in complex environments, integrating machine learning and computer vision technologies.

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Enhancing Image Annotation and Hand Detection Systems: Insights from Week 2 Presentations

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Presentation Transcript

  1. Cynthia Atherton REU Program: Week 2 Presentation

  2. Decisions, Decisions… • Annotation • Hand Detection

  3. Annotation Papers • “Automatically Annotating Images with Keywords: A Review of Image Annotation Systems” by Chih-Fong Tsai1,Department of Accounting and Information Technology, National Chung Cheng University, Taiwan, * and ChihliHung Department of Management Information Systems, Chung Yuan Christian University, Taiwan

  4. Annotation Paper Overview • Content-Based Image Retrieval (CBIR) systems extract and retrieve images by low-level features (e.g., color, texture, shape) but do not allow users to query images by semantic meanings The problem is that humans typically query images based on semantics • Image annotation systems annotate images with some controlled keywords • Machine learning techniques aid in the development of image annotation systems, mapping low-level (visual) features to high-level concepts or semantics

  5. Hand Detection Paper • “Recognizing American Sign Language Letters Using Principal Component Analysis”, by A. Geigelg http://geigel.com/signlanguage/paper.php Classification of sign language letters using Principal Component Analysis

  6. Research Project • Hand Detection • Computer vision/Machine learning • Communications/Culture

  7. Plan for near future • Continue absorbing “Hand Detection and Segmentation in Cluttered Environments” by Christopher Schwarz and Niels da Vitoria Lobo School of Computer Science, University of Central Florida, Orlando, FL • Learn the Code for the Hand Detection Program Java • Get with Alex Kachurin and Dr. Lobo to learn more

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