3D reconstruction of dynamic scenes with multiple handheld cameras
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Hierarchical object discovery and dense modelling from motion cues in RGB-D video
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
User assisted disparity remapping for stereo images
Image Communication
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This paper presents a novel multi-body multi-view stereo method to simultaneously recover dense depth maps and perform segmentation with the input of a monocular image sequence. Unlike traditional multi-view stereo approaches that generally handle a single static scene or an object, we show that depth estimation and segmentation can be jointly modeled and be globally solved in an energy minimization framework for ubiquitous scenes containing multiple independently moving rigid objects. Our major contribution includes a new multi-body stereo model, which integrates the color, geometry, and layer constraints for spatio-temporal depth recovery and automatic object segmentation. A two-pass optimization scheme is proposed to progressively update the estimates. Our method is applied to a variety of challenging examples.