Real-time 3D hand shape estimation based on inverse kinematics and physical constraints

Ryuji Fujiki, Daisaku Arita, Rin Ichiro Taniguchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

We are researching for real-time hand shape estimation, which we are going to apply to user interface and interactive applications. We have employed a computer vision approach, since unwired sensing provides restriction-free observation, or a natural way of sensing. The problem is that since a human hand has many joints, it has geometrically high degrees of freedom, which makes hand shape estimation difficult. For example, we have to deal with a self-occlusion problem and a large amount of computation. At the same time, a human hand has several physical constraints, i.e., each joint has a movable range and interdependence, which can potentially reduce the search space of hand shape estimation. This paper proposes a novel method to estimate 3D hand shapes in real-time by using shape features acquired from camera images and physical hand constraints heuristically introduced. We have made preliminary experiments using multiple cameras under uncomplicated background. We show experimental results in order to verify the effectiveness of our proposed method.

Original languageEnglish
Title of host publicationImage Analysis and Processing - ICIAP 2005, 13th International Conference, Proceedings
Pages850-858
Number of pages9
DOIs
Publication statusPublished - Dec 1 2005
Event13th International Conference on Image Analysis and Processing, ICIAP 2005 - Cagliari, Italy
Duration: Sep 6 2005Sep 8 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3617 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th International Conference on Image Analysis and Processing, ICIAP 2005
CountryItaly
CityCagliari
Period9/6/059/8/05

Fingerprint

Inverse Kinematics
Inverse kinematics
Real-time
Cameras
Sensing
Camera
Computer vision
Shape Feature
User interfaces
Occlusion
Computer Vision
Search Space
User Interface
Degree of freedom
Verify
Restriction
Experimental Results
Experiments
Estimate
Range of data

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Fujiki, R., Arita, D., & Taniguchi, R. I. (2005). Real-time 3D hand shape estimation based on inverse kinematics and physical constraints. In Image Analysis and Processing - ICIAP 2005, 13th International Conference, Proceedings (pp. 850-858). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3617 LNCS). https://doi.org/10.1007/11553595_104

Real-time 3D hand shape estimation based on inverse kinematics and physical constraints. / Fujiki, Ryuji; Arita, Daisaku; Taniguchi, Rin Ichiro.

Image Analysis and Processing - ICIAP 2005, 13th International Conference, Proceedings. 2005. p. 850-858 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3617 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Fujiki, R, Arita, D & Taniguchi, RI 2005, Real-time 3D hand shape estimation based on inverse kinematics and physical constraints. in Image Analysis and Processing - ICIAP 2005, 13th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3617 LNCS, pp. 850-858, 13th International Conference on Image Analysis and Processing, ICIAP 2005, Cagliari, Italy, 9/6/05. https://doi.org/10.1007/11553595_104
Fujiki R, Arita D, Taniguchi RI. Real-time 3D hand shape estimation based on inverse kinematics and physical constraints. In Image Analysis and Processing - ICIAP 2005, 13th International Conference, Proceedings. 2005. p. 850-858. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11553595_104
Fujiki, Ryuji ; Arita, Daisaku ; Taniguchi, Rin Ichiro. / Real-time 3D hand shape estimation based on inverse kinematics and physical constraints. Image Analysis and Processing - ICIAP 2005, 13th International Conference, Proceedings. 2005. pp. 850-858 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{a261ea7c83b24b87b3e071c3acf02e3a,
title = "Real-time 3D hand shape estimation based on inverse kinematics and physical constraints",
abstract = "We are researching for real-time hand shape estimation, which we are going to apply to user interface and interactive applications. We have employed a computer vision approach, since unwired sensing provides restriction-free observation, or a natural way of sensing. The problem is that since a human hand has many joints, it has geometrically high degrees of freedom, which makes hand shape estimation difficult. For example, we have to deal with a self-occlusion problem and a large amount of computation. At the same time, a human hand has several physical constraints, i.e., each joint has a movable range and interdependence, which can potentially reduce the search space of hand shape estimation. This paper proposes a novel method to estimate 3D hand shapes in real-time by using shape features acquired from camera images and physical hand constraints heuristically introduced. We have made preliminary experiments using multiple cameras under uncomplicated background. We show experimental results in order to verify the effectiveness of our proposed method.",
author = "Ryuji Fujiki and Daisaku Arita and Taniguchi, {Rin Ichiro}",
year = "2005",
month = "12",
day = "1",
doi = "10.1007/11553595_104",
language = "English",
isbn = "3540288694",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "850--858",
booktitle = "Image Analysis and Processing - ICIAP 2005, 13th International Conference, Proceedings",

}

TY - GEN

T1 - Real-time 3D hand shape estimation based on inverse kinematics and physical constraints

AU - Fujiki, Ryuji

AU - Arita, Daisaku

AU - Taniguchi, Rin Ichiro

PY - 2005/12/1

Y1 - 2005/12/1

N2 - We are researching for real-time hand shape estimation, which we are going to apply to user interface and interactive applications. We have employed a computer vision approach, since unwired sensing provides restriction-free observation, or a natural way of sensing. The problem is that since a human hand has many joints, it has geometrically high degrees of freedom, which makes hand shape estimation difficult. For example, we have to deal with a self-occlusion problem and a large amount of computation. At the same time, a human hand has several physical constraints, i.e., each joint has a movable range and interdependence, which can potentially reduce the search space of hand shape estimation. This paper proposes a novel method to estimate 3D hand shapes in real-time by using shape features acquired from camera images and physical hand constraints heuristically introduced. We have made preliminary experiments using multiple cameras under uncomplicated background. We show experimental results in order to verify the effectiveness of our proposed method.

AB - We are researching for real-time hand shape estimation, which we are going to apply to user interface and interactive applications. We have employed a computer vision approach, since unwired sensing provides restriction-free observation, or a natural way of sensing. The problem is that since a human hand has many joints, it has geometrically high degrees of freedom, which makes hand shape estimation difficult. For example, we have to deal with a self-occlusion problem and a large amount of computation. At the same time, a human hand has several physical constraints, i.e., each joint has a movable range and interdependence, which can potentially reduce the search space of hand shape estimation. This paper proposes a novel method to estimate 3D hand shapes in real-time by using shape features acquired from camera images and physical hand constraints heuristically introduced. We have made preliminary experiments using multiple cameras under uncomplicated background. We show experimental results in order to verify the effectiveness of our proposed method.

UR - http://www.scopus.com/inward/record.url?scp=33745117980&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33745117980&partnerID=8YFLogxK

U2 - 10.1007/11553595_104

DO - 10.1007/11553595_104

M3 - Conference contribution

AN - SCOPUS:33745117980

SN - 3540288694

SN - 9783540288695

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 850

EP - 858

BT - Image Analysis and Processing - ICIAP 2005, 13th International Conference, Proceedings

ER -