Fast constructive-solid geometry display in the pixel-powers graphics system
SIGGRAPH '86 Proceedings of the 13th annual conference on Computer graphics and interactive techniques
Generating octree models of 3D objects from their silhouettes in a sequence of images
Computer Vision, Graphics, and Image Processing
Rapid octree construction from image sequences
CVGIP: Image Understanding
How Far 3D Shapes Can Be Understood from 2D Silhouettes
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Interactive Boolean operations for conceptual design of 3-D solids
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detecting Salient Motion by Accumulating Directionally-Consistent Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction to Algorithms
Virtual View Generation for 3D Digital Video
IEEE MultiMedia
Reality Modeling and Visualization from Multiple Video Sequences
IEEE Computer Graphics and Applications
The Visual Hull Concept for Silhouette-Based Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking and Object Classification for Automated Surveillance
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Geometric modeling for computer vision.
Geometric modeling for computer vision.
IEEE Transactions on Pattern Analysis and Machine Intelligence
Convex Optimization
Segmentation and Tracking of Multiple Moving Objects for Intelligent Video Analysis
BT Technology Journal
Fusion of Multi-View Silhouette Cues Using a Space Occupancy Grid
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Statistical modeling of complex backgrounds for foreground object detection
IEEE Transactions on Image Processing
A survey of methods for volumetric scene reconstruction from photographs
VG'01 Proceedings of the 2001 Eurographics conference on Volume Graphics
Shape from silhouette using Dempster-Shafer theory
Pattern Recognition
Shape from incomplete silhouettes based on the reprojection error
Image and Vision Computing
Improved 3D reconstruction in smart-room environments using ToF imaging
Computer Vision and Image Understanding
Shape from pairwise silhouettes for plan-view map generation
Image and Vision Computing
Shape from Silhouette Consensus
Pattern Recognition
An octree-based method for shape from inconsistent silhouettes
Pattern Recognition
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Shape from silhouette (SfS) is the general term used to refer to the techniques that obtain a volume estimate from a set of binary images. In a first step, a number of images are taken from different positions around the scene of interest. Later, each image is segmented to produce binary masks, also called silhouettes, to delimit the objects of interest. Finally, the volume estimate is obtained as the maximal one which yields the silhouettes. The set of silhouettes is usually considered to be consistent which means that there exists at least one volume which completely explains them. However, silhouettes are normally inconsistent due to inaccurate calibration or erroneous silhouette extraction techniques. In spite of that, SfS techniques reconstruct only that part of the volume which projects consistently in all the silhouettes, leaving the rest unreconstructed. In this paper, we extend the idea of SfS to be used with sets of inconsistent silhouettes. We propose a fast technique for estimating that part of the volume which projects inconsistently and propose a criteria for classifying it by minimizing the probability of miss-classification taking into account the 2D error detection probabilities of the silhouettes. A number of theoretical and empirical results are given, showing that the proposed method reduces the reconstruction error.