摘要
This paper presents a handheld 3D vision-based scanner for small objects by using Kinect. It is different from the previous color-glove-based approaches which require segmenting the target object. First, we eliminate the noises and the outliers caused by holding hands. Second, we apply Kinect-fusion algorithm and truncated signed distance function （TSDF） to represent 3D surfaces. Third, we propose a modified integration strategy to eliminate the hand effect. Fourth, we take advantage of the parallel computation of GPUs for real-time operation. The major contributions of this paper are （1） the registration precision is improved, （2） the oflline amendment and loop closure operation are not required, and （3） concave 3D object reconstruction is feasible.
This paper presents a handheld 3D vision-based scanner for small objects by using Kinect. It is different from the previous color-glove-based approaches which require segmenting the target object. First, we eliminate the noises and the outliers caused by holding hands. Second, we apply Kinect-fusion algorithm and truncated signed distance function （TSDF） to represent 3D surfaces. Third, we propose a modified integration strategy to eliminate the hand effect. Fourth, we take advantage of the parallel computation of GPUs for real-time operation. The major contributions of this paper are （1） the registration precision is improved, （2） the oflline amendment and loop closure operation are not required, and （3） concave 3D object reconstruction is feasible.
基金
supported by the Ministry of Science and Technology of Taiwan under Grant No.MOST103-2221-E-468-006–MY1
