Gradient-based modified census transform for optical flow

Authors:
Philipp Puxbaum;Kristian Ambrosch
Affiliations:
AIT Austrian Institute of Technology, Vienna, Austria;AIT Austrian Institute of Technology, Vienna, Austria
Venue:
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
Year:
2010

Citing 6
Cited 1

Non-parametric local transforms for computing visual correspondence

ECCV '94 Proceedings of the third European conference on Computer Vision (Vol. II)
Determining Optical Flow

Determining Optical Flow
Robust Real-Time Face Detection

International Journal of Computer Vision
A Roadmap to the Integration of Early Visual Modules

International Journal of Computer Vision
Flexible Architecture for Three Classes of Optical Flow Extraction Algorithms

RECONFIG '08 Proceedings of the 2008 International Conference on Reconfigurable Computing and FPGAs
Face detection with the modified census transform

FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition

Distortion compensation for movement detection based on dense optical flow

ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

To enable the precise detection of persons walking or running on the ground using unmannedMicro Aerial Vehicles (MAVs), we present the evaluation of the MCT algorithm based on intensity as well as gradient images for optical flow, focusing on accuracy as well as low computational complexity to enable the real-time implementation in light-weight embedded systems. Therefore, we give a detailed analysis of this algorithm on four optical flow datasets from the Middlebury database and show the algorithm's performance when compared to other optical flow algorithms. Furthermore, different approaches for sub-pixel refinement and occlusion detection are discussed.