Reliable and Efficient Computation of Optical Flow
International Journal of Computer Vision
Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods
International Journal of Computer Vision
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Towards Ultimate Motion Estimation: Combining Highest Accuracy with Real-Time Performance
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Particle Video: Long-Range Motion Estimation using Point Trajectories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Particle Video: Long-Range Motion Estimation Using Point Trajectories
International Journal of Computer Vision
An Improved Algorithm for TV-L1 Optical Flow
Statistical and Geometrical Approaches to Visual Motion Analysis
A duality based approach for realtime TV-L1 optical flow
Proceedings of the 29th DAGM conference on Pattern recognition
GPU-based multigrid: real-time performance in high resolution nonlinear image processing
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Feature tracking and matching in video using programmable graphics hardware
Machine Vision and Applications
Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
On convergence of the Horn and Schunck optical-flow estimation method
IEEE Transactions on Image Processing
Parallel computing with patterns and frameworks
XRDS: Crossroads, The ACM Magazine for Students - The Changing Face of Programming
Object segmentation by long term analysis of point trajectories
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Copperhead: compiling an embedded data parallel language
Proceedings of the 16th ACM symposium on Principles and practice of parallel programming
International Journal of Computer Vision
SimpleFlow: A Non-iterative, Sublinear Optical Flow Algorithm
Computer Graphics Forum
Real time semi-dense point tracking
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part I
Background subtraction using low rank and group sparsity constraints
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Active frame selection for label propagation in videos
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Two-granularity tracking: mediating trajectory and detection graphs for tracking under occlusions
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Online moving camera background subtraction
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Stixels motion estimation without optical flow computation
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Semi-Nonnegative matrix factorization for motion segmentation with missing data
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VII
SuperFloxels: a mid-level representation for video sequences
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
Consistent Binocular Depth and Scene Flow with Chained Temporal Profiles
International Journal of Computer Vision
Video segmentation with superpixels
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Adaptive integration of feature matches into variational optical flow methods
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Robust object tracking using constellation model with superpixel
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Scalable multimedia content analysis on parallel platforms using python
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
User-assisted sparse stereo-video segmentation
Proceedings of the 10th European Conference on Visual Media Production
Detecting bipedal motion from correlated probabilistic trajectories
Pattern Recognition Letters
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Dense and accurate motion tracking is an important requirement for many video feature extraction algorithms. In this paper we provide a method for computing point trajectories based on a fast parallel implementation of a recent optical flow algorithm that tolerates fast motion. The parallel implementation of large displacement optical flow runs about 78× faster than the serial C++ version. This makes it practical to use in a variety of applications, among them point tracking. In the course of obtaining the fast implementation, we also proved that the fixed point matrix obtained in the optical flow technique is positive semi-definite. We compare the point tracking to the most commonly used motion tracker - the KLT tracker - on a number of sequences with ground truth motion. Our resulting technique tracks up to three orders of magnitude more points and is 46% more accurate than the KLT tracker. It also provides a tracking density of 48% and has an occlusion error of 3% compared to a density of 0.1% and occlusion error of 8% for the KLT tracker. Compared to the Particle Video tracker, we achieve 66% better accuracy while retaining the ability to handle large displacements while running an order of magnitude faster.