Name
Abstract | ||
|---|---|---|
In this paper, we present a system for indoor human localization that does not need 3D reconstruction of features or landmarks. We assume that a video sequence has been acquired and that keyframes have been registered with respect to 2D positions and orientations. In online mode, we use only a handheld monochrome fisheye camera and a synchronized IMU as sensory inputs. The query is not based on a single image but uses a HMM-based state estimator. Our image representation consists of initial global GIST vectors followed by local SURF features. We present a novel approach to localization by using search space reduction on global features, then HMM based position prediction and estimation on local features. Experimental results show that accurate localization is achieved and realtime performance is feasible. This work demonstrates that a working portable system could be designed for the visually impaired. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/CVPRW.2010.5543581 | Computer Vision and Pattern Recognition Workshops |
Keywords | Field | DocType |
feature extraction,handicapped aids,hidden markov models,image representation,position control,search problems,state estimation,video signal processing,3d mapping,gist vector,hmm-based state estimator,imu,surf feature,hidden markov model,indoor human localization,monochrome fisheye camera,video sequence,video-based localization,visually impaired,image reconstruction,estimation,lighting,3d reconstruction,geometry,navigation,global positioning system,search space | Iterative reconstruction,Computer vision,Pattern recognition,Computer science,Monochrome,Feature extraction,Mobile device,Global Positioning System,Artificial intelligence,Inertial measurement unit,Hidden Markov model,3D reconstruction | Conference |
Volume | Issue | ISSN |
2010 | 1 | 2160-7508 |
ISBN | Citations | PageRank |
978-1-4244-7029-7 | 13 | 0.63 |
References | Authors | |
21 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jason J. Liu | 1 | 13 | 0.63 |
| Cody J. Phillips | 2 | 45 | 4.80 |
| Konstantinos Daniilidis | 3 | 3122 | 255.45 |