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Estimating dense 3D scene flow from stereo sequences remains a challenging task, despite much progress in both classical disparity and 2D optical flow estimation. To overcome the limitations of existing techniques, we introduce a novel model that represents the dynamic 3D scene by a collection of planar, rigidly moving, local segments. Scene flow estimation(More)
Motion estimation in realistic outdoor settings is significantly challenged by cast shadows, reflections, glare, saturation, automatic gain control, etc. To allow robust optical flow estimation in these cases, it is important to choose appropriate data cost functions for matching. Recent years have seen a growing trend toward patch-based data costs, as they(More)
Our ability to predict whether elevated atmospheric CO 2 will alter the cycling of C and N in terrestrial ecosystems requires understanding a complex set of feedback mechanisms initiated by changes in C and N acquisition by plants and the degree to which changes in resource acquisition (C and N) alter plant growth and allocation. To gain further insight(More)
3D scene flow estimation aims to jointly recover dense geometry and 3D motion from stereoscopic image sequences, thus generalizes classical disparity and 2D optical flow estimation. To realize its conceptual benefits and overcome limitations of many existing methods, we propose to represent the dynamic scene as a collection of rigidly moving planes, into(More)
We present an approach to 3D scene flow estimation, which exploits that in realistic scenarios image motion is frequently dominated by observer motion and independent, but rigid object motion. We cast the dense estimation of both scene structure and 3D motion from sequences of two or more views as a single energy minimization problem. We show that agnostic(More)
We propose a method to recover dense 3D scene flow from stereo video. The method estimates the depth and 3D motion field of a dynamic scene from multiple consecutive frames in a sliding temporal window, such that the estimate is consistent across both viewpoints of all frames within the window. The observed scene is modeled as a collection of planar patches(More)
Understanding the relationships between climate and carbon exchange by terrestrial ecosystems is critical to predict future levels of atmospheric carbon dioxide because of the potential accelerating effects of positive climate–carbon cycle feedbacks. However, directly observed relationships between climate and terrestrial CO 2 exchange with the atmosphere(More)
In an increasing number of applications triangle meshes represent a flexible and efficient alternative to traditional NURBS-based surface representations. Especially in engineering applications it is crucial to guarantee that a prescribed approximation tolerance to a given reference geometry is respected for any combination of geometric algorithms that are(More)
We propose an adaptive multi-resolution formulation of semantic 3D reconstruction. Given a set of images of a scene, semantic 3D reconstruction aims to densely reconstruct both the 3D shape of the scene and a segmentation into semantic object classes. Jointly reasoning about shape and class allows one to take into account class-specific shape priors (e.g.,(More)
Temporal changes in plant tissue non-structural carbohydrates (NSC) may be sensitive to climate changes that alter forest phenology. We examined how temporal fluctuations in tissue NSC concentrations of Populus grandidentata and Quercus rubra relate to net and gross primary production (NPP, GPP) and their climatic drivers in a deciduous forest of Michigan,(More)