Study of Analyzing Dynamical Behaviors and 3D Reconstruction from Video Sequences
| Project/Area Number |
22500167
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Perception information processing/Intelligent robotics
|
|---|
| Research Institution | Waseda University |
|---|
Principal Investigator |
OHYA Jun 早稲田大学, 理工学術院, 教授 (90329152)
|
|---|
| Project Period (FY) |
2010 – 2012
|
| Project Status |
Completed (Fiscal Year 2012)
|
| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2012: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2011: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2010: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
|
|---|
| Keywords | コンピュータビジョン / 動画像処理 / 行動認識 / ベイジアンネットワーク / 手話認識 / 表情 / 動的カメラ / 動物体 / 追跡 / ３次元復元 / 表情認識 / パーティクルフィルター / 手振り認識 / 3次元復元 / 修正RANSAC / 動画像 / 移動カメラ / 樹木 / テンソル分解 |
|---|
| Research Abstract |
Among many research topics related to video sequence analysis, this research focuses on the following topics: (1) Human posture estimation, (2) Tracking and recognizing humans, (3) Pose estimation of a moving camera and 3D reconstruction, and (4) Analysis of botanical trees’ behaviors. In (1), we study a method that utilizes results of detedting the user’s postures of the face, hand and fingers for human interface between a large screen, showing effectiveness of the proposed method. In (2), we explore human tracking and action recognition by a tensor analysis based method, recognition of customers’ behaviors in shops by a Bayesian Network based method, and Condenstation algorithm based recognition of sign langues’ vocabularies that use facial expressions and hand gestures. In (3), we research how to detect moving objects from dynamic video sequences and to reconstruct 3D structure of the detected objects, showing the validity of the proposed method. In (4), we study how to track a leaf in front of other leaves using a Particle filter, showing promising results.
|
Report
(4 results)
Research Products
(59 results)
