- 专利标题: LEARNING METHOD AND LEARNING DEVICE FOR REMOVING JITTERING ON VIDEO ACQUIRED THROUGH SHAKING CAMERA BY USING A PLURALITY OF NEURAL NETWORKS FOR FAULT TOLERANCE AND FLUCTUATION ROBUSTNESS IN EXTREME SITUATIONS, AND TESTING METHOD AND TESTING DEVICE USING THE SAME
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申请号: EP20150915.5申请日: 2020-01-09
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公开(公告)号: EP3690811A1公开(公告)日: 2020-08-05
- 发明人: KIM, Kye-Hyeon , KIM, Yongjoong , KIM, Insu , KIM, Hak-Kyoung , NAM, Woonhyun , BOO, SukHoon , SUNG, Myungchul , YEO, Donghun , RYU, Wooju , JANG, Taewoong , JEONG, Kyungjoong , JE, Hongmo , CHO, Hojin
- 申请人: StradVision, Inc.
- 申请人地址: Suite 304-308, 5th Venture-dong 394, Jigok-ro Nam-gu Pohang-si Gyeongsangbuk-do 37668 KR
- 专利权人: StradVision, Inc.
- 当前专利权人: StradVision, Inc.
- 当前专利权人地址: Suite 304-308, 5th Venture-dong 394, Jigok-ro Nam-gu Pohang-si Gyeongsangbuk-do 37668 KR
- 代理机构: Vossius & Partner Patentanwälte Rechtsanwälte mbB
- 优先权: US201916262996 20190131
- 主分类号: G06T7/246
- IPC分类号: G06T7/246 ; G06K9/32 ; G06K9/40 ; G06N3/04 ; G06K9/46 ; G06N3/08 ; G06T5/00
摘要:
A method for detecting jittering in videos generated by a shaken camera to remove the jittering on the videos using neural networks is provided for fault tolerance and fluctuation robustness in extreme situations. The method includes steps of: a computing device, generating each of t-th masks corresponding to each of objects in a t-th image; generating each of t-th object motion vectors of each of object pixels, included in the t-th image by applying at least one 2-nd neural network operation to each of the t-th masks, each of t-th cropped images, each of (t-1)-th masks, and each of (t-1)-th cropped images; and generating each of t-th jittering vectors corresponding to each of reference pixels among pixels in the t-th image by referring to each of the t-th object motion vectors. Thus, the method is used for video stabilization, object tracking with high precision, behavior estimation, motion decomposition, etc.
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