Multidimensional Orientation Estimation with Applications to Texture Analysis and Optical Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generic Neighborhood Operators
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance of optical flow techniques
International Journal of Computer Vision
Direct computation of shape cues using scale-adapted spatial derivative operators
International Journal of Computer Vision - Special issue: machine vision research at the Royal Institute of Technology
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation
International Journal of Computer Vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
Evaluation of Interest Point Detectors
International Journal of Computer Vision - Special issue on a special section on visual surveillance
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
ASSET-2: Real-Time Motion Segmentation and Shape Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space with Casual Time Direction
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Combining Appearance and Topology for Wide Baseline Matching
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
An Affine Invariant Interest Point Detector
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
On Automatic Selection of Temporal Scales in Time-Causal Scale-Space
AFPAC '97 Proceedings of the International Workshop on Algebraic Frames for the Perception-Action Cycle
Motion Feature Detection Using Steerable Flow Fields
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2
Real-time scale selection in hybrid multi-scale representations
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
Fingerprint enhancement by shape adaptation of scale-space operators with automatic scale selection
IEEE Transactions on Image Processing
International Journal of Computer Vision
Nonlinear multiscale analysis of motion trajectories
ICCVG'10 Proceedings of the 2010 international conference on Computer vision and graphics: Part I
Spatiotemporal saliency detection and salient region determination for H.264 videos
Journal of Visual Communication and Image Representation
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Several types of interest point detectors have been proposed for spatial images. This paper investigates how this notion can be generalised to the detection of interesting events in space-time data. Moreover, we develop a mechanism for spatio-temporal scale selection and detect events at scales corresponding to their extent in both space and time. To detect spatio-temporal events, we build on the idea of the Harris and Förstner interest point operators and detect regions in space-time where the image structures have significant local variations in both space and time. In this way, events that correspond to curved space-time structures are emphasised, while structures with locally constant motion are disregarded. To construct this operator, we start from a multi-scale windowed second moment matrix in space-time, and combine the determinant and the trace in a similar way as for the spatial Harris operator. All spacetime maxima of this operator are then adapted to characteristic scales by maximising a scale-normalised space-time Laplacian operator over both spatial scales and temporal scales. The motivation for performing temporal scale selection as a complement to previous approaches of spatial scale selection is to be able to robustly capture spatio-temporal events of different temporal extent. It is shown that the resulting approach is truly scale invariant with respect to both spatial scales and temporal scales. The proposed concept is tested on synthetic and real image sequences. It is shown that the operator responds to distinct and stable points in space-time that often correspond to interesting events. The potential applications of the method are discussed.