Abstract
In this paper, we present our recent sensor fusion approaches to obtain high-quality 3D information. We first discuss two fusion methods that combine geometric and photometric information. The first method, multiview photometric stereo, reconstructs the full 3D shape of a target object. The geometric and photometric information is efficiently fused by using a planar mesh representation. The second method performing shape-from shading with a Kinect sensor estimates the shape of an object under uncalibrated natural illumination. Since the method uses a single RGB-D input, it is capable of capturing the high quality shape details of a dynamic object under varying illumination. Subsequently, we summarize a calibration algorithm of a time of-flight (ToF) sensor and a camera fusion system with a 2.5D pattern. Lastly, we present a camera-laser sensor fusion system for the large-scale 3D reconstruction.
Original language | English |
---|---|
Pages | 6-10 |
Number of pages | 5 |
DOIs | |
State | Published - 2013 |
Event | 2013 2nd IAPR Asian Conference on Pattern Recognition, ACPR 2013 - Naha, Okinawa, Japan Duration: 5 Nov 2013 → 8 Nov 2013 |
Conference
Conference | 2013 2nd IAPR Asian Conference on Pattern Recognition, ACPR 2013 |
---|---|
Country/Territory | Japan |
City | Naha, Okinawa |
Period | 5/11/13 → 8/11/13 |