Name
Title | ||
|---|---|---|
Probabilistic Multi-modal People Tracker and Monocular Pointing Pose Estimator for Visual Instruction of Mobile Robot Assistants |
Abstract | ||
|---|---|---|
In this paper, we present two important aspects of our human-robot communication interface which is being developed in the context of our long-term research framework PERSES dealing with the development of highly interactive mo- bile robotic assistants. First, we introduce a multi-modal people detection and tracking system, a fundamental prerequisite for the observation of a human interaction partner and his non- verbal instructions given by pointing poses, gestures, head pose and eye gaze. Based on this detection and tracking system, we present a hierarchical neural architecture that is capable of estimating a target point at the floor given a pointing pose, thus enabling a user to command his mobile robot to a specific target position in his local surroundings by means of pointing. In this context, we were especially interested in determining whether it is possible to accomplish such a target point estimator using only monocular images of low-cost cameras. Both the tracker and the target point estimator were implemented and experi- mentally investigated on our mobile robotic assistant HOROS. The achieved recognition results presented finally demonstrate that it is in fact possible to realize a user-independent pointing pose estimation using monocular images only, but further efforts are necessary to improve the robustness of this approach for everyday application. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/IJCNN.2006.246971 | Vancouver, BC |
Keywords | Field | DocType |
control engineering computing,man-machine systems,mobile robots,neural net architecture,pose estimation,tracking,PERSES,hierarchical neural architecture,human-robot communication interface,interactive mobile robotic assistants,low-cost cameras,mobile robot assistants,monocular images,monocular pointing pose estimator,multimodal people detection,probabilistic multimodal people tracker,research framework,tracking system,visual instruction | Computer vision,Gesture,Computer science,Tracking system,Robustness (computer science),Pose,Eye tracking,Artificial intelligence,Probabilistic logic,Monocular,Mobile robot | Conference |
ISSN | ISBN | Citations |
2161-4393 | 0-7803-9490-9 | 5 |
PageRank | References | Authors |
0.62 | 11 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gross, H.-M. | 1 | 5 | 0.62 |
| Richarz, J. | 2 | 5 | 0.62 |
| Mueller, S. | 3 | 24 | 1.51 |
| Scheidig, A. | 4 | 5 | 0.62 |