Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Finding Boundaries in Natural Images: A New Method Using Point Descriptors and Area Completion
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Smoothness in Layers: Motion segmentation using nonparametric mixture estimation.
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A multi-body factorization method for motion analysis
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Motion Segmentation and Tracking Using Normalized Cuts
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Layered Motion Segmentation and Depth Ordering by Tracking Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion Competition: A Variational Approach to Piecewise Parametric Motion Segmentation
International Journal of Computer Vision
Motion Layer Extraction in the Presence of Occlusion Using Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Level Grouping for Video Shots
International Journal of Computer Vision
Unsupervised Bayesian Detection of Independent Motion in Crowds
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Learning Layered Motion Segmentations of Video
International Journal of Computer Vision
Particle Video: Long-Range Motion Estimation Using Point Trajectories
International Journal of Computer Vision
Clustering Point Trajectories with Various Life-Spans
CVMP '09 Proceedings of the 2009 Conference for Visual Media Production
Dense point trajectories by GPU-accelerated large displacement optical flow
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Learning semantic scene models by trajectory analysis
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Detachable object detection with efficient model selection
EMMCVPR'11 Proceedings of the 8th international conference on Energy minimization methods in computer vision and pattern recognition
Probabilistic models for robot-based object segmentation
Robotics and Autonomous Systems
Extracting intentionally captured regions using point trajectories
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Video object segmentation with shortest path
Proceedings of the 20th ACM international conference on Multimedia
Learning common behaviors from large sets of unlabeled temporal series
Image and Vision Computing
Multi-scale clustering of frame-to-frame correspondences for motion segmentation
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Coherent filtering: detecting coherent motions from crowd clutters
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
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
Semi-Nonnegative matrix factorization for motion segmentation with missing data
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VII
Weakly supervised learning of object segmentations from web-scale video
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
Towards feature-based situation assessment for airport apron video surveillance
Proceedings of the 15th international conference on Theoretical Foundations of Computer Vision: outdoor and large-scale real-world scene analysis
SuperFloxels: a mid-level representation for video sequences
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
Motion-Based segmentation for cardiomyocyte characterization
STIA'12 Proceedings of the Second international conference on Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data
Video segmentation with superpixels
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Online learning for fast segmentation of moving objects
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Dynamic objectness for adaptive tracking
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Learning object appearance from occlusions using structure and motion recovery
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Learning a quality-based ranking for feature point trajectories
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Motion segmentation by velocity clustering with estimation of subspace dimension
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
Background subtraction via coherent trajectory decomposition
Proceedings of the 21st ACM international conference on Multimedia
Editor's Choice Article: Motion-based segmentation of objects using overlapping temporal windows
Image and Vision Computing
Multi-object reconstruction from dynamic scenes: An object-centered approach
Computer Vision and Image Understanding
Integrating tracking with fine object segmentation
Image and Vision Computing
User-assisted sparse stereo-video segmentation
Proceedings of the 10th European Conference on Visual Media Production
Activity representation with motion hierarchies
International Journal of Computer Vision
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Unsupervised learning requires a grouping step that defines which data belong together. A natural way of grouping in images is the segmentation of objects or parts of objects. While pure bottom-up segmentation from static cues is well known to be ambiguous at the object level, the story changes as soon as objects move. In this paper, we present a method that uses long term point trajectories based on dense optical flow. Defining pair-wise distances between these trajectories allows to cluster them, which results in temporally consistent segmentations of moving objects in a video shot. In contrast to multi-body factorization, points and even whole objects may appear or disappear during the shot. We provide a benchmark dataset and an evaluation method for this so far uncovered setting.