Robotics and Computer Vision Lab

Publications

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저 자 Gyeongmin Choe, Jaesik Park, Yu-Wing Tai, In So Kweon
학 회 International Journal of Computer Vision (IJCV)
Notes This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2010-0028680).
논문일시(Year) 2016
논문일시(Month) 09
http://link.springer.com/article/10.1007/s11263-016-0937-y?wt_mc=Internal.Event.1.SEM.ArticleAuthorOnlineFirstWe propose a method to refine geometry of 3D meshes from a consumer level depth camera, e.g. Kinect, by exploiting shading cues captured from an infrared (IR) camera. A major benefit to using an IR camera instead of an RGB camera is that the IR images captured are narrow band images that filter out most undesired ambient light, which makes our system robust against natural indoor illumination. Moreover, for many natural objects with colorful textures in the visible spectrum, the subjects appear to have a uniform albedo in the IR spectrum. Based on our analyses on the IR projector light of the Kinect, we define a near light source IR shading model that describes the captured intensity as a function of surface normals, albedo, lighting direction, and distance between light source and surface points. To resolve the ambiguity in our model between the normals and distances, we utilize an initial 3D mesh from the Kinect fusion and multiview information to reliably estimate surface details that were not captured and reconstructed by the Kinect fusion. Our approach directly operates on the mesh model for geometry refinement. We ran experiments on our algorithm for geometries captured by both the Kinect I and Kinect II, as the depth acquisition in Kinect I is based on a structured-light technique and that of the Kinect II is based on a time-of-flight technology. The effectiveness of our approach is demonstrated through several challenging real-world examples. We have also performed a user study to evaluate the quality of the mesh models before and after our refinements.

List of Articles
585. DeepPTZ: Deep Self-Calibration for PTZ Cameras
Chaoning Zhang, Francois Rameau, Junsik Kim, Dawit Mureja Argaw, Jean-Charles Bazin, and In So Kweon
IEEE Winter Conference on Applications of Computer Vision (WACV) 2020 / 03
584. Propose-and-Attend Single Shot Detector
Ho-Deok Jang, Sanghyun Woo, Philipp Benz, Jinsun Park, and In So Kweon
IEEE Winter Conference on Applications of Computer Vision (WACV) 2020 / 03
583. Ring Difference Filter for Fast and Noise Robust Depth from Focus
Hae-Gon Jeon, Jaeheung Surh, Sunghoon Im, In So Kweon
IEEE Transactions Image Processing (TIP) 2019 / 8
582. Deep Iterative Frame Interpolation for Full-frame Video Stabilization
Jinsoo Choi, In So Kweon
ACM Transactions on Graphics (TOG) / SIGGRAPH Asia 2019 / 11
581. Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach
Dong-Jin Kim, Jinsoo Choi, Tae-Hyun Oh, In So Kweon
International Conference on Empirical Methods in Natural Language Processing (EMNLP) 2019 / 11
580. Visuomotor Understanding for Representation Learning of Driving Scenes
Seokju Lee, Junsik Kim, Tae-Hyun Oh, Yongseop Jeong, Donggeun Yoo, Stephen Lin, In So Kweon
British Machine Vision Conference (BMVC) 2019 / 9
579. Revisiting Residual Networks with Nonlinear Shortcuts
Chaoning Zhang, Francois Rameau, Seokju Lee, Junsik Kim, Philipp Benz, Dawit Mureja Argaw, Jean-Charles Bazin, In So Kweon
British Machine Vision Conference (BMVC) 2019 / 9
578. Fast Perception, Planning, and Execution for a Robotic Butler: Wheeled Humanoid M-Hubo
Moonyoung Lee, Yujin Heo, Jinyong Park, Hyundae Yang, Ho-Deok Jang, Philipp Benz, Hyunsub Park, In So Kweon and Jun-Ho Oh
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE 2019 / 11
577. One-Day Outdoor Photometric Stereo Using Skylight Estimation
Jiyoung Jung, Joon-Young Lee, In So Kweon
International Journal of Computer Vision (IJCV) 2019 / 8
576. Vehicular Multi-Camera Sensor System for Automated Visual Inspection of Electric Power Distribution Equipment
Jinsun Park, Ukcheol Shin, Gyumin Shim, Kyungdon Joo, Francois Rameau, Junhyeok Kim, Dong-Geol Choi and In So Kweon
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE 2019 / 11
575. Camera Exposure Control for Robust Robot Vision with Noise-Aware Image Quality Assessment
Ukcheol Shin, Jinsun Park, Gyumin Shim, Francois Rameau, and In So Kweon
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE 2019 / 11
574. Learning Residual Flow as Dynamic Motion from Stereo Videos
Seokju Lee, Sunghoon Im, Stephen Lin, and In So Kweon
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE 2019 / 11
573. DISC: A Large-scale Virtual Dataset for Simulating Disaster Scenarios
Hae-Gon Jeon, Sunghoon Im, Byeong-Uk Lee, Dong-Geol Choi, Martial Hebert, and In So Kweon
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE 2019 / 11
572. Preserving Semantic and Temporal Consistency for Unpaired Video-to-Video Translation
Kwanyong Park, Sanghyun Woo, Dahun Kim, Donghyeon Cho, In So Kweon
27th ACM International Conference on Multimedia 2019 / 10
571. Video Retargeting: Trade-off between Content Preservation and Spatio-temporal Consistency
Donghyeon Cho, Yunjae Jung, Francois Rameau, Dahun Kim, Sanghyun Woo and In So Kweon
27th ACM International Conference on Multimedia 2019 / 10
570. Segment2Regress: Monocular 3D Vehicle Localization in Two Stages
Jaesung Choe, Kyungdon Joo, Francois Rameau, Gyumin Shim, In So Kweon
Robotics: Science and Systems (RSS) 2019 / 06
569. Globally Optimal Inlier Set Maximization for Atlanta World Understanding
Kyungdon Joo, Tae-Hyun Oh, In So Kweon, Jean-Charles Bazin
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2019 / 3
568. Deep Video Inpainting
Dahun Kim, Sanghyun Woo, Joon-Young Lee, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019 / 07
567. Deep Blind Video Decaptioning by Temporal Aggregation and Recurrence
Dahun Kim, Sanghyun Woo, Joon-Young Lee, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019 / 07
566. Dense Relational Captioning: Triple-Stream Networks for Relationship-Based Captioning
Dong-Jin Kim, Jinsoo Choi, Tae-Hyun Oh, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019 / 07
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