In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Unified Approach to Moving Object Detection in 2D and 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Independent Motion Detection in 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Tracking with Bayesian Estimation of Dynamic Layer Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmenting Foreground Objects from a Dynamic Textured Background via a Robust Kalman Filter
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Statistical Background Subtraction for a Mobile Observer
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A Unified Framework for Tracking through Occlusions and across Sensor Gaps
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Motion Layer Extraction in the Presence of Occlusion Using Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection and Tracking of Moving Objects from a Moving Platform in Presence of Strong Parallax
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
KNIGHT/spl trade/: a real time surveillance system for multiple and non-overlapping cameras
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Matching actions in presence of camera motion
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion-based background subtraction using adaptive kernel density estimation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
On the Analysis of Accumulative Difference Pictures from Image Sequences of Real World Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image segmentation in video sequences: a probabilistic approach
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Representing moving images with layers
IEEE Transactions on Image Processing
Hi-index | 0.00 |
In this paper we present a novel approach for detection of independently moving foreground objects in non-planar scenes captured by a moving camera. We avoid the traditional assumptions that the stationary background of the scene is planar, or that it can be approximated by dominant single or multiple planes, or that the camera used to capture the video is orthographic. Instead we utilize a multiframe monocular epipolar constraint of camera motion derived for monocular moving cameras defined by an evolving epipolar plane between the moving camera center and 3D scene points. This constraint is parameterized as a polynomial function of time, and unlike repeated computations of inter-frame fundamental matrix, requires the estimation of fewer unknowns, and provides a more consistent separation between moving and static objects for different levels of noise. This constraint allows us to segment out moving objects in a general 3D scene where other approaches fail because their initial assumptions do not hold, and provides a natural way of fusing temporal information across multiple frames. We use a combination of optical flow and particle advection to capture all motion in the video across a number of frames, in the form of particle trajectories. We then apply the derived multi-frame epipolar constraint to these trajectories to determine which trajectories violate it, thus segmenting out the independently moving objects. We show superior results on a number of moving camera sequences observing non-planar scenes, where other methods fail.