2026-09-18T21:56:48Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/986242022-01-18T17:16:50Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Andrew B. Lippman.
Niles, Savannah
Massachusetts Institute of Technology. Department of Architecture. Program in Media Arts and Sciences.
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
2015-09-17T19:00:26Z
2015-09-17T19:00:26Z
2015
2015
http://hdl.handle.net/1721.1/98624
920474747
Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2015.
Cataloged from PDF version of thesis.
Includes bibliographical references.
There is an emotional dimension to the informative function of the news. When we read the news we participate in a collective emotional experience- whether that is grief, celebration, worry, or wonder. News video is a crucial vector for these shared emotional experiences, which can propel civic action. But video comes at a high cost in time and attention, and is thus unsuitable for high volume news and social feeds, and mobile and wearable devices. On these interfaces, there is value in presenting video in a way that's immediately evocative, preserving the richness of video while atomizing it to an excerpt as "glanceable" as a still image. This thesis proposes Glyph, a tool for creating expressive, seamlessly-looping GIFs from video. The tool integrates opensource software for video/image manipulation and loop detection into a simple, web-based authoring interface. Glyph allows a user to automatically detect perfect loops that occur in a video, create the appearance of seamless motion in a non-looping clip, still some regions of movement in a clip to highlight others, or imbue a still frame with subtle dynamism. The part-automated, part-manual editing tool thus allows users to quickly build nonliteral excerpts from video that can immediately crystalize an affective quality or crucial moment, suspending and intensifying its semantic or emotional content through continuous, seamless looping. This thesis additionally explores applications for this class of image, called glyphs.
by Savannah Niles.
S.M.
101 pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Architecture. Program in Media Arts and Sciences.
Glyph : lightweight and evocative looping images in the news
Lightweight and evocative looping images in the news
Thesis
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<Abstract>There is an emotional dimension to the informative function of the news. When we read the news we participate in a collective emotional experience- whether that is grief, celebration, worry, or wonder. News video is a crucial vector for these shared emotional experiences, which can propel civic action. But video comes at a high cost in time and attention, and is thus unsuitable for high volume news and social feeds, and mobile and wearable devices. On these interfaces, there is value in presenting video in a way that's immediately evocative, preserving the richness of video while atomizing it to an excerpt as "glanceable" as a still image. This thesis proposes Glyph, a tool for creating expressive, seamlessly-looping GIFs from video. The tool integrates opensource software for video/image manipulation and loop detection into a simple, web-based authoring interface. Glyph allows a user to automatically detect perfect loops that occur in a video, create the appearance of seamless motion in a non-looping clip, still some regions of movement in a clip to highlight others, or imbue a still frame with subtle dynamism. The part-automated, part-manual editing tool thus allows users to quickly build nonliteral excerpts from video that can immediately crystalize an affective quality or crucial moment, suspending and intensifying its semantic or emotional content through continuous, seamless looping. This thesis additionally explores applications for this class of image, called glyphs.</Abstract>
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