Name
Abstract | ||
|---|---|---|
Memory deterioration is a common problem, and the locations of household objects such as remote controls, medicine bottles, and teacups are sometimes forgotten despite being in frequent use. To enhance the quality of life and reduce the amount of time wasted locating these objects, this study employs depth cameras for object tracking, segmentation, and recognition using color and depth data captured in the images and positions of objects during interaction with the skeleton of a hand. This process establishes an index of features relative to object positions that can be used to assist the user in recalling the location of household objects. Preliminary experiments have demonstrated promising performance of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICMLC48188.2019.8949227 | 2019 International Conference on Machine Learning and Cybernetics (ICMLC) |
Keywords | Field | DocType |
Depth camera,Feature index,Object recall,Recognition,Segmentation | Medicine bottles,Pattern recognition,Segmentation,Computer science,Video tracking,Artificial intelligence,Recall | Conference |
ISSN | ISBN | Citations |
2160-133X | 978-1-7281-2817-7 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chin-Pan Huang | 1 | 57 | 7.56 |
| Chaur-Heh Hsieh | 2 | 354 | 46.89 |
| Chu-Cheng Huang | 3 | 0 | 0.34 |