자료유형 | 학위논문 |
---|---|
서명/저자사항 | Data-driven Approaches for Personalized Head Reconstruction. |
개인저자 | Liang, Shu. |
단체저자명 | University of Washington. Computer Science and Engineering. |
발행사항 | [S.l.]: University of Washington., 2018. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
형태사항 | 111 p. |
기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
ISBN | 9780438176843 |
학위논문주기 | Thesis (Ph.D.)--University of Washington, 2018. |
일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Linda G. Shapiro. |
요약 | Personalized 3D face reconstruction has produced exciting results over the past few years. However, traditional methods usually require complicated setups or controlled environments to get the detailed shape of a person's face. Most methods focu |
요약 | The first part of our work introduces an algorithm that takes a single frame of a person's face from a commercial depth camera Kinect and produces a high-resolution 3D mesh of the input leveraging a large research dataset of 3D face meshes. We d |
요약 | In order to free people from the capturing session, the larger portion of this thesis focuses on reconstructing not only the face, but also the rest of the head using in-the-wild image collections and videos. We first introduce a boundary-value |
요약 | Results on photos of celebrities downloaded from the Internet are given. However, in this algorithm, we have not reconstructed a complete head model and a specific model of the hair is lacked. |
요약 | We further utilize a person's in-the-wild video to recover the full head model considering the multi-view information and hairstyle consistency across video frames. Given a video of a person's head, e.g., a TV interview, our method automatically |
일반주제명 | Computer science. |
언어 | 영어 |
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