Coherent intrinsic images from photo collections
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Video enhancement leveraging high-quality depth maps
Proceedings of the 11th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry
Low-Cost and open-source solutions for automated image orientation --- a critical overview
EuroMed'12 Proceedings of the 4th international conference on Progress in Cultural Heritage Preservation
Dense scene reconstruction with points of interest
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
Large-Scale bundle adjustment by parameter vector partition
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
Adaptive structure from motion with a contrario model estimation
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
3D reconstruction for damaged documents: imaging of the great parchment book
Proceedings of the 2nd International Workshop on Historical Document Imaging and Processing
Advanced Engineering Informatics
Augmented and interactive video playback based on global camera pose
Proceedings of the 21st ACM international conference on Multimedia
3D Wikipedia: using online text to automatically label and navigate reconstructed geometry
ACM Transactions on Graphics (TOG)
A non-parametric unsupervised approach for content based image retrieval and clustering
Proceedings of the 4th ACM/IEEE international workshop on Analysis and retrieval of tracked events and motion in imagery stream
Where should I stand? Learning based human position recommendation for mobile photographing
Multimedia Tools and Applications
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We present the design and implementation of new inexact Newton type Bundle Adjustment algorithms that exploit hardware parallelism for efficiently solving large scale 3D scene reconstruction problems. We explore the use of multicore CPU as well as multicore GPUs for this purpose. We show that overcoming the severe memory and bandwidth limitations of current generation GPUs not only leads to more space efficient algorithms, but also to surprising savings in runtime. Our CPU based system is up to ten times and our GPU based system is up to thirty times faster than the current state of the art methods, while maintaining comparable convergence behavior. The code and additional results are available at http://grail.cs.washington.edu/projects/mcba.