Journal ArticleDOI
When is the shape of a scene unique given its light-field: a fundamental theorem of 3D vision?
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TLDR
It is shown that stereo computed from the light-field is ambiguous if and only if the scene is radiating light of a constant intensity (and color, etc.) over an extended region.Abstract:
The complete set of measurements that could ever be used by a passive 3D vision algorithm is the plenoptic function or light-field. We give a concise characterization of when the light-field of a Lambertian scene uniquely determines its shape and, conversely, when the shape is inherently ambiguous. In particular, we show that stereo computed from the light-field is ambiguous if and only if the scene is radiating light of a constant intensity (and color, etc.) over an extended region.read more
Citations
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Proceedings ArticleDOI
A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms
TL;DR: This paper first survey multi-view stereo algorithms and compare them qualitatively using a taxonomy that differentiates their key properties, then describes the process for acquiring and calibrating multiview image datasets with high-accuracy ground truth and introduces the evaluation methodology.
Journal ArticleDOI
Spacetime stereo: a unifying framework for depth from triangulation
TL;DR: It is shown that methods derived from the spacetime stereo framework can be used to recover depth in situations in which existing methods perform poorly.
Journal ArticleDOI
Appearance-based face recognition and light-fields
TL;DR: A theory of appearance-based object recognition from light-fields is developed, which leads directly to an algorithm for face recognition across pose that uses as many images of the face as are available, from one upwards.
Proceedings ArticleDOI
Spacetime stereo: a unifying framework for depth from triangulation
TL;DR: It is shown that methods derived from the spacetime stereo framework can be used to recover depth in situations in which existing methods perform poorly.
Journal ArticleDOI
Automated as-built 3D reconstruction of civil infrastructure using computer vision
TL;DR: This paper aims to analyze the state-of-the-art in image-based 3D reconstruction and categorize existing algorithms according to different metrics that are important for the given purpose and a list of practical constraints that make the3D reconstruction of infrastructure a challenging task is presented.
References
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Proceedings ArticleDOI
Light field rendering
Marc Levoy,Pat Hanrahan +1 more
TL;DR: This paper describes a sampled representation for light fields that allows for both efficient creation and display of inward and outward looking views, and describes a compression system that is able to compress the light fields generated by more than a factor of 100:1 with very little loss of fidelity.
Book
Robot Vision
TL;DR: Robot Vision as discussed by the authors is a broad overview of the field of computer vision, using a consistent notation based on a detailed understanding of the image formation process, which can provide a useful and current reference for professionals working in the fields of machine vision, image processing, and pattern recognition.
Proceedings ArticleDOI
The lumigraph
TL;DR: A new method for capturing the complete appearance of both synthetic and real world objects and scenes, representing this information, and then using this representation to render images of the object from new camera positions.
Journal ArticleDOI
The visual hull concept for silhouette-based image understanding
TL;DR: This paper addresses the problem of finding which parts of a nonconvex object are relevant for silhouette-based image understanding and introduces the geometric concept of visual hull of a 3-D object, which is the maximal object silhouette-equivalent to S.
The Plenoptic Function and the Elements of Early Vision
TL;DR: Early vision as discussed by the authors is defined as measuring the amounts of various kinds of visual substances present in the image (e.g., redness or rightward motion energy) rather than in how it labels "things".