Koichi Ogawara — accepted AI-conference papers

2022

Segmentation and Shape Estimation of Multiple Deformed Cloths Using a CNN-Based Landmark Detector and Clustering

ICRA 2022poster

In this paper, we propose a method for segmentation and shape estimation of multiple deformed cloths stacked on a floor from an image using a CNN-based landmark detector and clustering. The proposed method first estimates landmark positions from the heatmaps generated from the landmark detector and…

Cited by 0 Source ↗Scholar ↗

2020

Estimation of object class and orientation from multiple viewpoints and relative camera orientation constraints

Koichi Ogawara, Keita Iseki

IROS 2020poster

In this research, we propose a method of estimating object class and orientation given multiple input images assuming the relative camera orientations are known. Input images are transformed to descriptors on 2-D manifolds defined for each class of object through a CNN, and the object class and orie…

Cited by 2 Source ↗Scholar ↗