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Titlebook: Computer Vision – ACCV 2016 Workshops; ACCV 2016 Internatio Chu-Song Chen,Jiwen Lu,Kai-Kuang Ma Conference proceedings 2017 Springer Intern

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樓主: 烹飪
41#
發(fā)表于 2025-3-28 18:28:40 | 只看該作者
Comparison of Kinect V1 and V2 Depth Images in Terms of Accuracy and Precisionamera or the scene color. Furthermore, we demonstrate errors like . and .. Our insights build the basis for incorporating or modeling the errors of the devices in follow-up algorithms for diverse applications.
42#
發(fā)表于 2025-3-28 20:47:50 | 只看該作者
43#
發(fā)表于 2025-3-29 02:23:06 | 只看該作者
44#
發(fā)表于 2025-3-29 06:53:05 | 只看該作者
3D Shape Reconstruction in Traffic Scenarios Using Monocular Camera and Lidarpose and shape are jointly optimized. A significant performance improvement by the proposed approach in estimating object 3D orientation and the occupancy bounding box is proven through quantitative evaluation.
45#
發(fā)表于 2025-3-29 09:58:29 | 只看該作者
DSLIC: A Superpixel Based Segmentation Algorithm for Depth Imagean adaptation of Simple Linear Iterative Clustering (SLIC) with a novel utilization of depth and gradient direction as an alternate of LaB color space features. Our novel approach is demonstrated perform favorably to over-segment large planar area in an unlit environment.
46#
發(fā)表于 2025-3-29 14:17:36 | 只看該作者
47#
發(fā)表于 2025-3-29 19:34:32 | 只看該作者
3D Line Segment Reconstruction in Structured Scenes via Coplanar Line Segment Clusteringwe formulate to solve the LS match grouping problem into solving a multi-label optimization problem. The advantages of the proposed algorithm over others in this area are that it can generate more complete and detailed 3D models of scenes using much fewer images and can recover the space planes wher
48#
發(fā)表于 2025-3-29 23:36:22 | 只看該作者
49#
發(fā)表于 2025-3-30 03:19:36 | 只看該作者
50#
發(fā)表于 2025-3-30 05:24:47 | 只看該作者
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