Feature tracking and matching in video using programmable graphics hardware

Authors:
Sudipta N. Sinha;Jan-Michael Frahm;Marc Pollefeys;Yakup Genc
Affiliations:
University of North Carolina at Chapel Hill, Department of Computer Science, CB# 3175 Sitterson Hall, 27599, Chapel Hill, NC, USA;University of North Carolina at Chapel Hill, Department of Computer Science, CB# 3175 Sitterson Hall, 27599, Chapel Hill, NC, USA;University of North Carolina at Chapel Hill, Department of Computer Science, CB# 3175 Sitterson Hall, 27599, Chapel Hill, NC, USA;Siemens Corporate Research, Real-time Vision and Modeling Department, 755 College Road East, 08540, Princeton, NJ, USA
Venue:
Machine Vision and Applications
Year:
2011

Citing 0
Cited 16

Detailed Real-Time Urban 3D Reconstruction from Video

International Journal of Computer Vision
A mapping and localization framework for scalable appearance-based navigation

Computer Vision and Image Understanding
Recognizing places using spectrally clustered local matches

Robotics and Autonomous Systems
A Hardware Architecture for SIFT Candidate Keypoints Detection

CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Accelerating mobile augmented reality on a handheld platform

ICCD'09 Proceedings of the 2009 IEEE international conference on Computer design
Dense point trajectories by GPU-accelerated large displacement optical flow

ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Real-time stereo reconstruction in robotically assisted minimally invasive surgery

MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
A parallel analysis on scale invariant feature transform (SIFT) algorithm

APPT'11 Proceedings of the 9th international conference on Advanced parallel processing technologies
Accelerating SIFT on hybrid clusters

Proceedings of the ACM SIGSPATIAL Second International Workshop on High Performance and Distributed Geographic Information Systems
Gyro-aided feature tracking for a moving camera: fusion, auto-calibration and GPU implementation

International Journal of Robotics Research
High-performance template tracking

Journal of Visual Communication and Image Representation
Real-time optical SLAM-based mosaicking for unmanned underwater vehicles

Intelligent Service Robotics
GPU accelerated image processing for lip segmentation

PPAM'11 Proceedings of the 9th international conference on Parallel Processing and Applied Mathematics - Volume Part I
Real time semi-dense point tracking

ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part I
Accelerating visual categorization with the GPU

ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part II
A high-performance, low-energy FPGA accelerator for correntropy-based feature tracking (abstract only)

Proceedings of the ACM/SIGDA international symposium on Field programmable gate arrays

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes novel implementations of the KLT feature tracking and SIFT feature extraction algorithms that run on the graphics processing unit (GPU) and is suitable for video analysis in real-time vision systems. While significant acceleration over standard CPU implementations is obtained by exploiting parallelism provided by modern programmable graphics hardware, the CPU is freed up to run other computations in parallel. Our GPU-based KLT implementation tracks about a thousand features in real-time at 30 Hz on 1,024 × 768 resolution video which is a 20 times improvement over the CPU. The GPU-based SIFT implementation extracts about 800 features from 640 × 480 video at 10 Hz which is approximately 10 times faster than an optimized CPU implementation.