Generating octree models of 3D objects from their silhouettes in a sequence of images
Computer Vision, Graphics, and Image Processing
A survey of construction and manipulation of octrees
Computer Vision, Graphics, and Image Processing
Stereoscopic tracking of bodies in motion
Image and Vision Computing - Special issue: 5th Alvey vision meeting
Rapid octree construction from image sequences
CVGIP: Image Understanding
Artificial Intelligence
Automatic Model Construction and Pose Estimation From Photographs Using Triangular Splines
IEEE Transactions on Pattern Analysis and Machine Intelligence
Acquiring 3-D Models from Sequences of Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Visual Hull Concept for Silhouette-Based Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Non-parametric Model for Background Subtraction
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Geometric modeling for computer vision.
Geometric modeling for computer vision.
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
Shape from inconsistent silhouette
Computer Vision and Image Understanding
Shape from silhouette using Dempster-Shafer theory
Pattern Recognition
Describing a Robot's Workspace Using a Sequence of Views from a Moving Camera
IEEE Transactions on Pattern Analysis and Machine Intelligence
Volumetric Descriptions of Objects from Multiple Views
IEEE Transactions on Pattern Analysis and Machine Intelligence
Foreground regions extraction and characterization towards real-time object tracking
MLMI'05 Proceedings of the Second international conference on Machine Learning for Multimodal Interaction
A new decision-making method by incomplete preferences based on evidence distance
Knowledge-Based Systems
| Hi-index | 0.01 |
Shape-from-Silhouette (SfS) is the widely known problem of obtaining the 3D structure of an object from its silhouettes. Two main approaches can be employed: those based on voxel sets, which perform an exhaustive search of the working space, and those based on octrees, which perform a top-down analysis that speeds up the computation. The main problem of both approaches is the need for perfect silhouettes to obtain accurate results. Perfect background subtraction hardly ever happens in realistic scenarios, so these techniques are restricted to controlled environments where the consistency hypothesis can be assumed. Recently, some approaches (all of them based on voxel sets) have been proposed to solve the problem of inconsistency. Their main drawback is the high computational cost required to perform an exhaustive analysis of the working space. This paper proposes a novel approach to solve SfS with inconsistent silhouettes from an octree based perspective. The inconsistencies are dealt by means of the Dempster-Shafer (DS) theory and we employ a Butterworth function for adapting threshold values in each resolution level of the octree. The results obtained show that our proposal provides higher reconstruction quality than the standard octree based methods in realistic environments. When compared to voxel set approaches that manage inconsistency, our method obtains similar results with a reduction in the computing time of an order of magnitude.