Study on a novel modeling system for non-stationary objects such as fruit trees in the outdoor environment
| Project/Area Number |
26450366
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Research Field |
Agricultural environmental engineering/Agricultural information engineering
|
|---|
| Research Institution | Wakayama University |
|---|
Principal Investigator |
|
|---|
| Project Period (FY) |
2014-04-01 – 2017-03-31
|
| Project Status |
Completed (Fiscal Year 2016)
|
| Budget Amount *help |
¥5,070,000 (Direct Cost: ¥3,900,000、Indirect Cost: ¥1,170,000)
Fiscal Year 2016: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2015: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2014: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
|
|---|
| Keywords | スキャンマッチング / CIF特徴量 / 共振ミラー方式三次元測域センサ / 3次元スキャナー / ハイパースペクトルカメラ / 順序保存統合 / 超高感度カメラ / ライトフィールドカメラ |
|---|
| Outline of Final Research Achievements |
In order to detect invariant features from multiple three dimensional data acquired under the outdoor environment, we conducted experiments using three kinds of cameras with different characteristics. As a result of investigating various conditions necessary for detecting the invariant feature, it was found that it can be used as a useful invariant feature by adjusting the generation parameters of such invariant feature which was previously proposed.
As a preparation method of robustly stitching mltiple three-dimensional data, we proposed a measure representing its shape of two-dimensional range data. We also proposed a method for robustly stitching multiple two-dimensional range data, which uses the measure to decide whether to include useful shape features of the environment in the two-dimensional range data and has our SVM classifier learn to conduct such judgement.
|
Report
(4 results)
Research Products
(5 results)
