Proceedings of IEEE International Conference on Computer Vision
DOI: 10.1109/iccv.1995.466927
|View full text |Cite
|
Sign up to set email alerts
|

Structure and motion estimation from dynamic silhouettes under perspective projection

Abstract: We address the problem of estimating the structure and motion of a smooth curved object from its silhouettes observed over time by a trinocular stereo rig under perspective projection. We first construct a model for the local structure along the silhouette for each frame in the temporal sequence. The local models are then integrated into a global surface description by estimating the motion between successive time instants. The algorithm tracks certain surface features (parabolic points) and image features (si… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
26
0

Publication Types

Select...
4
3

Relationship

1
6

Authors

Journals

citations
Cited by 38 publications
(26 citation statements)
references
References 21 publications
(14 reference statements)
0
26
0
Order By: Relevance
“…By combining the ideas in [14] and [16], Cross et al implemented a parallax-based technique [17] in which images are registered using a reference plane to "undo" the effect of rotation. Related works also include [18] and [19].…”
Section: Previous Workmentioning
confidence: 99%
“…By combining the ideas in [14] and [16], Cross et al implemented a parallax-based technique [17] in which images are registered using a reference plane to "undo" the effect of rotation. Related works also include [18] and [19].…”
Section: Previous Workmentioning
confidence: 99%
“…An approach for parallel projection has been presented in (Vijaykumar et al, 1995, 52Åström, Cipolla and. Another approach using trinocular stereo has been presented in (Joshi et al, 1995).…”
Section: Introductionmentioning
confidence: 99%
“…Methods for recovering both the surface structure and the camera motion using a trinocular rig have been proposed by Vaillant and Faugeras [35] and Joshi et al [18]. The single-camera case is more difficult, and the algorithms proposed by Giblin et al [15], Mendonca et al [26], and Wong and Cipolla [38] are limited to circular camera motions.…”
Section: Introductionmentioning
confidence: 99%