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Volume 05 No. 04
05 December 2019

Taishi Ono, Hiroyuki Kubo, Kenichiro Tanaka, Takuya Funatomi, Yasuhiro Mukaigawa

2019, 05(04): 325-336.   doi:10.1007/s41095-019-0150-3
Abstract ( 86 HTML ( 7   PDF(23208KB) ( 29 )   Save

In this paper, we present a practical methodfor reconstructing the bidirectional reflectance distribu-tion function (BRDF) from multiple images of a real object composed of a homogeneous material. The key idea is that the BRDF can be sampled after geometry estimation using multi-view stereo (MVS) techniques. Our contribution is selection of reliable samples of lighting, surface normal, and viewing directions for robustness against estimation errors of MVS. Our method is quantitatively evaluat...

Weijie Xi, Xuejin Chen

2019, 05(04): 337-345.   doi:10.1007/s41095-019-0159-7
Abstract ( 35 HTML ( 2   PDF(11394KB) ( 139 )   Save

Reconstruction of man-made scenes from multi-view images is an important problem in computer vision and computer graphics. Observing that man-made scenes are usually composed of planar surfaces, we encode plane shape prior in reconstructing man-made scenes. Recent approaches for single-view reconstruction employ multi-branch neural networks to simultaneouslysegment planes and recover 3D plane parameters. However, the scale of available annotated data heavily limits the generalizability and ac...

Taye Girma Debelee, Friedhelm Schwenker, Samuel Rahimeto, Dereje Yohannes

2019, 05(04): 347-361.   doi:10.1007/s41095-019-0151-2
Abstract ( 67 HTML ( 0   PDF(13536KB) ( 17 )   Save

Segmentation is the act of partitioning an image into different regions by creating boundaries between regions. k-means image segmentation is the simplest prevalent approach. However, the segmentation quality is contingent on the initial parameters (the cluster centers and their number). In this paper, a convolution-based modified adaptive

Ruotong Li, Weixin Si, Xiangyun Liao, Qiong Wang, Reinhard Klein, Pheng-Ann Heng

2019, 05(04): 363-374.   doi:10.1007/s41095-019-0156-x
Abstract ( 49 HTML ( 0   PDF(14522KB) ( 11 )   Save

This paper presents a novel mixed reality based navigation system for accurate respiratory liver tumor punctures in radiofrequency ablation (RFA). Oursystem contains an optical see-through head-mounted display device (OST-HMD), Microsoft HoloLens for perfectly overlaying the virtual information on the patient, and a optical tracking system NDI Polaris for calibrating the surgical utilities in the surgical scene. Compared with traditional navigation method with CT, our system aligns the virtua...

Yaohua Pan, Zhibin Niu, Jing Wu, Jiawan Zhang

2019, 05(04): 375-390.   doi:10.1007/s41095-019-0157-9
Abstract ( 37 HTML ( 0   PDF(14457KB) ( 10 )   Save

Role-event videos are rich in information but challenging to be understood at the story level. The social roles and behavior patterns of characters largely depend on the interactions among characters and the background events. Understanding them requires analysisof the video contents for a long duration, which is beyond the ability of current algorithms designed for analyzing short-time dynamics. In this paper, we propose InSocialNet, an interactive video analytics tool for analyzing the cont...

Shuai Liu, Ruipeng Gang, Chenghua Li, Ruixia Song

2019, 05(04): 391-401.   doi:10.1007/s41095-019-0158-8
Abstract ( 46 HTML ( 1   PDF(17705KB) ( 36 )   Save

In recent years, deep learning has achieved great success in the field of image processing. In the single image super-resolution (SISR) task, the con-volutional neural network (CNN) extracts the features of the image through deeper layers, and has achieved impressive results. In this paper, we propose a singleimage super-resolution model based on Adaptive Deep Residual named as ADR-SR, which uses the Input Output Same Size (IOSS) structure, and releases the dependence of upsampling layers com...

Ruochen Fan, Xuanrun Wang, Qibin Hou, Hanchao Liu, Tai-Jiang Mu

2019, 05(04): 417-428.   doi:10.1007/s41095-019-0152-1
Abstract ( 67 HTML ( 0   PDF(10147KB) ( 31 )   Save

In this paper, we propose a simple but effective framework for lane boundary detection, called SpinNet. Considering that cars or pedestrians often occlude lane boundaries and that the local features of lane boundaries are not distinctive, therefore, analyzing and collecting global context information is crucial for lane boundary detection. To this end, we design a novel spinning convolution layer and a brand-new lane parameterization branch in our network to detect lane boundaries from a glob...