TY - GEN
T1 - High-speed depth stream generation from a hybrid camera
AU - Zuo, Xinxin
AU - Wang, Sen
AU - Zheng, Jiangbin
AU - Yang, Ruigang
N1 - Publisher Copyright:
© 2016 ACM.
PY - 2016/10/1
Y1 - 2016/10/1
N2 - High-speed video has been commonly adopted in consumergrade cameras, augmenting these videos with a corresponding depth stream will enable new multimedia applications, such as 3D slow-motion video. In this paper, we present a hybrid camera system that combines a high-speed color camera with a depth sensor, e.g. Kinect depth sensor, to generate a depth stream that can produce both high-speed and high-resolution RGB+depth stream. Simply interpolating the low-speed depth frames is not satisfactory, where interpolation artifacts and lose in surface details are often visible. We have developed a novel framework that utilizes both shading constraints within each frame and optical ow constraints between neighboring frames. More specifically we present (a) an effective method to find the intrinsics images to allow more accurate normal estimation; and (b) an optimization-based framework to estimate the high-resolution/high-speed depth stream, taking into consideration temporal smoothness and shading/depth consistency. We evaluated our holistic framework with both synthetic and real sequences, it showed superior performance than previous state-of-the-art.
AB - High-speed video has been commonly adopted in consumergrade cameras, augmenting these videos with a corresponding depth stream will enable new multimedia applications, such as 3D slow-motion video. In this paper, we present a hybrid camera system that combines a high-speed color camera with a depth sensor, e.g. Kinect depth sensor, to generate a depth stream that can produce both high-speed and high-resolution RGB+depth stream. Simply interpolating the low-speed depth frames is not satisfactory, where interpolation artifacts and lose in surface details are often visible. We have developed a novel framework that utilizes both shading constraints within each frame and optical ow constraints between neighboring frames. More specifically we present (a) an effective method to find the intrinsics images to allow more accurate normal estimation; and (b) an optimization-based framework to estimate the high-resolution/high-speed depth stream, taking into consideration temporal smoothness and shading/depth consistency. We evaluated our holistic framework with both synthetic and real sequences, it showed superior performance than previous state-of-the-art.
KW - Depth stream
KW - High-speed imaging
KW - Intrinisic decomposition
KW - Shape from shading
UR - http://www.scopus.com/inward/record.url?scp=84994560259&partnerID=8YFLogxK
U2 - 10.1145/2964284.2964305
DO - 10.1145/2964284.2964305
M3 - 会议稿件
AN - SCOPUS:84994560259
T3 - MM 2016 - Proceedings of the 2016 ACM Multimedia Conference
SP - 878
EP - 887
BT - MM 2016 - Proceedings of the 2016 ACM Multimedia Conference
PB - Association for Computing Machinery, Inc
T2 - 24th ACM Multimedia Conference, MM 2016
Y2 - 15 October 2016 through 19 October 2016
ER -