Robotics and Computer Vision Lab

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International Journal
2017.10.19 16:30

Geometry Guided 3D Propagation for Depth from Small Motion

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저 자 Seunghak Shin, Sunghoon Im, Inwook Shim, Hae-Gon Jeon, In So Kweon
학 회 IEEE Signal Processing Letters
Notes This work was supported by the “Development of core technology for advanced locomotion/manipulation based on high-speed/power robot platform and robot intelligence,” project from the Korea Evaluation Institute of Industrial Technology of the Republic of Korea. The work of S. Im and H.-G. Jeon was supported in part by Global Ph.D. Fellowship Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education under Grant NRF-2016907531 and Grant NRF-2015034617.
논문일시(Year) 2017
논문일시(Month) 12
http://ieeexplore.ieee.org/document/8063412/In this letter, we present an accurate Depth from Small Motion approach, which reconstructs three-dimensional (3-D) depth from image sequences with extremely narrow base-lines.We start with estimating sparse 3-D points and camera poses via the structure from motion method. For dense depth reconstruction, we propose a novel depth propagation using a geometric guidance term that considers not only the geometric constraint from the surface normal, but also color consistency. In addition, we propose an accurate surface normal estimation method with a multiple range search so that the normal vector can guide the direction of the depth propagation precisely. The major benefit of our depth propagation method is that it obtains detailed structures of a scene without fronto-parallel bias.We validate our method using various indoor and outdoor datasets, and both qualitative and quantitative experimental results show that our new algorithm consistently generates better 3-D depth information than the results of existing state-of-the-art methods.

List of Articles
» Geometry Guided 3D Propagation for Depth from Small Motion
Seunghak Shin, Sunghoon Im, Inwook Shim, Hae-Gon Jeon, In So Kweon
IEEE Signal Processing Letters 2017 / 12
530. Intelligent Assistant for People with Low Vision Abilities
Oleksandr Bogdan, Oleg Yurchenko, Oleksandr Bailo, Francois Rameau, Donggeun Yoo, In So Kweon
The 8th Pacific Rim Symposium on Image and Video Technology (PSIVT) 2017 / 11
529. Multi-Scale, Multi-Object and Real-Time Face Detection and Head Pose Estimation Using Deep Neural Networks
Byungtae Ahn, Dong-Geol Choi, In So Kweon
Journal of Korea Robotics Society 2017 / 09
528. VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition
Seokju Lee, Junsik Kim, Jae Shin Yoon, Seunghak Shin, Oleksandr Bailo, Namil Kim, Tae-Hee Lee, Hyun Seok Hong, Seung-Hoon Han, In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
527. Two-Phase Learning for Weakly Supervised Object Localization
Dahun Kim, Donghyeon Cho, Donggeun Yoo, In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
526. Weakly- and Self- Supervised Learning for Content-Aware Deep Image Retargeting
Donghyeon Cho, Jinsun Park, Tae-Hyun Oh, Yu-Wing Tai, In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
525. Deltille Grids for Geometric Camera Calibration
Hyowon Ha, Michal Perdoch, Hatem Alismail, In So Kweon, Yaser Sheikh
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
524. Personalized Cinemagraphs using Semantic Understanding and Collaborative Learning
Tae-Hyun Oh, Kyungdon Joo, Neel Joshi, Baoyuan Wang, In So Kweon, Sing Bing Kang
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
523. Noise Robust Depth From Focus Using a Ring Difference Filter
Jaeheung Surh, Hae-Gon Jeon, Yunwon Park, Sunghoon Im, Hyowon Ha, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017 / 07
522. Pixel-Level Matching for Video Object Segmentation using Convolutional Neural Networks
Jae Shin Yoon, Francois Rameau, Junsik Kim, Seokju Lee, Seunghak Shin, In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
521. A Real-Time and Energy-Efficient Embedded System for Intelligent ADAS with RNN-Based Deep Risk Prediction using Stereo Camera
Kyuho Lee, Gyeongmin Choe, Kyeongryeol Bong, Changhyeon Kim, In So Kweon, Hoi-Jun Yoo
International Conference on Computer Vision Systems (ICVS) 2017 / 07
520. A Closed-Form Solution to Rotation Estimation for Structure from Small Motion
Hyowon Ha, Tae-Hyun Oh, In So Kweon
IEEE Signal Processing Letters 2017 / 05
519. Local deformation calibration for autostereoscopic 3D display
Hyoseok Hwang, Hyun Sung Chang, In So Kweon
OSA Optics Express 2017 / 05
518. A Unified Approach of Multi-scale Deep and Hand-crafted Features for Defocus Estimation
Jinsun Park, Yu-Wing Tai, Donghyeon Cho, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017 / 07
517. Multi-Image Deblurring using Complementary Sets of Fluttering Patterns
Hae-Gon Jeon, Joon-Young Lee, Yudeog Han, Seon Joo Kim, In So Kweon
IEEE Transactions on Image Processing 2017 / 05
516. Light Field Image Super-Resolution using Convolutional Neural Network
Youngjin Yoon, Hae-Gon Jeon, Donggeun Yoo, Joon-Young Lee, In So Kweon
IEEE Signal Processing Letters 2017 / 02
515. Structure-From-Motion in 3D Space Using 2D Lidars
Dong-Geol Choi, Yunsu Bok, Jun-sik Kim, Inwook Shim, In So Kweon
Sensors 2017 / 02
514. Deep Representation of Industrial Components using Simulated Images
Seong-Heum Kim, Gyeongmin Choe, Byungtae Ahn, In So Kweon
IEEE International Conference on Robotics and Automation (ICRA) 2017 / 05
513. 3D Display Calibration by Visual Pattern Analysis
Hyoseok Hwang, Hyun Sung Chang, Dongkyung Nam, In So Kweon
IEEE Transactions on Image Processing (TIP), accepted 2017 / 02
512. Single Image Depth Estimation using Convolutional Neural Networks with NCC-based Loss
Jinsun Park, In So Kweon
International Workshop on Frontiers of Computer Vision (FCV) 2017 / 02
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