Authors:
Rafael F. V. Saracchini
1
;
Carlos Catalina
1
;
Rodrigo Minetto
2
and
Jorge Stolfi
3
Affiliations:
1
Technological Institute of Castilla y León, Spain
;
2
Federal University of Technology of Paraná, Brazil
;
3
State University of Campinas, Brazil
Keyword(s):
3D Tracking, Augmented Reality, Camera Calibration, Real-time and GPU Processing.
Related
Ontology
Subjects/Areas/Topics:
Active and Robot Vision
;
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Enterprise Information Systems
;
Entertainment Imaging Applications
;
Human and Computer Interaction
;
Human-Computer Interaction
;
Image and Video Analysis
;
Image Formation and Preprocessing
;
Image Formation, Acquisition Devices and Sensors
;
Image Registration
;
Motion, Tracking and Stereo Vision
;
Optical Flow and Motion Analyses
;
Stereo Vision and Structure from Motion
Abstract:
In this paper we describe VOPT, a robust algorithm for visual odometry. It tracks features of the environment
with known position in space, which can be acquired through monocular or RGBD SLAM mapping
algorithms. The main idea of VOPT is to jointly optimize the matching of feature projections on successive
frames, the camera’s extrinsic matrix, the photometric correction parameters, and the weight of each feature
at the same time, by a multi-scale iterative procedure. VOPT uses GPU acceleration to achieve real-time performance,
and includes robust procedures for automatic initialization and recovery, without user intervention.
Our tests show that VOPT outperforms the PTAMM algorithm in challenging videos available publicly.