Friday Lunch Seminar (English)<\/p>\n\n\n\n

January 20, 2023
12:15 \u301c 13:00
(On-line)
Apply for participation from here<\/a> by noon, January 19.
You will be notified of participation details by e-mail on January 19.

Talk Title: Intelligent Visual Transfer<\/p>\n\n\n\n

Hideo Yokota
Team Leader
Image Processing Research Team
Center for Advanced Photonics
RIKEN <\/p>\n\n\n\n

Abstract:
Image transfer is an important underlying technology for video distribution and web conferencing. This data is much more voluminous than textual or numerical delivery and requires very large bandwidth to transfer the data. In recent years, the increasing transfer of video data has become a problem for data transfer over the Internet and cell phones. Therefore, we are developing a new method of image data transfer. Our focus is on the acquisition and recognition of human images. We have mimicked the way image acquisition in the human eye and image recognition in the brain occurs. In this talk, I will present a brief introduction to the image transfer methods we are developing.<\/strong>

Talk Title: Feature-aware Image Filtering and its Applications<\/p>\n\n\n\n

Shin Yoshizawa
Senior Scientist
Image Processing Research Team
Center for Advanced Photonics
RIKEN <\/p>\n\n\n\n

Abstract:
Digital image consists of salient edges and texture structures, and therefore feature-aware image filters, which remove image structures smaller than a specific scale while preserving salient edges, are important and useful in many image processing and computer vision applications. In this talk, I will present a brief introduction to feature-aware image filtering and its applications including detail enhancement, denoising, seamless cloning, HDRI displaying, matting, and stylization.

Talk Title: Visual Saliency Guided Image Compression for Telepresence Robotics System<\/p>\n\n\n\n

Sun Zhe
Research Scientist
Image Processing Research Team
Center for Advanced Photonics
RIKEN <\/p>\n\n\n\n

Abstract:
Over the past decade, communication technologies and image\/video compression approaches have been improved significantly. However, the connection bandwidth in specific conditions, such as from satellite\/airborne to earth stations, is still insufficient. Here we propose a visual importance map-guided framework for image\/video compression. Inspired by human visual system, the importance map is constructed by the saliency (perceptual attention) and gradient maps (geometric edge) for each image.<\/p>\n\n\n\n

Host PI: Takashi Fujikado<\/a><\/p>\n\n\n\n

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