We propose a novel approach to tracking objects by low-level line correspondences. In our implementation we show that this approach is usable even when tracking objects with lack of texture, exploiting situations, when feature-based trackers fails due to the aperture problem. Furthermore, we suggest an approach to failure detection and recovery to maintain long-term stability. This is achieved by remembering configurations which lead to good pose estimations and using them later for tracking corrections. We carried out experiments on several sequences of different types. The proposed tracker proves itself as competitive or superior to state-of-the-art trackers in both standard and low-textured scenes. © 2013 Springer-Verlag
Cameras can naturally capture sequences of images, or videos, and for computers to understand videos...
This paper presents an efficient camera tracking using prior knowledge of a target scene?3-D object ...
International audienceWe consider the problem of tracking a given set of point features over large s...
We propose a novel approach to tracking objects by low-level line correspondences. In our implementa...
We propose a novel approach to tracking objects by low-level line correspondences. In our implementa...
Long term tracking of an object, given only a single in-stance in an initial frame, remains an open ...
Long term tracking of an object, given only a single instance in an initial frame, remains an open p...
Long term tracking of an object, given only a single instance in an initial frame, remains an open p...
Feature points and object edges are two kinds of primitives which are frequently used in target trac...
Most modern object trackers combine a motion prior with sliding-window detection, using binary class...
Visual tracking of unknown objects in unconstrained video-sequences is extremely challenging due to ...
We present a markerless tracking approach for augmented reality in poorly textured environments. The...
This thesis proposes a robust on-line tracking method by 1) enlarging the convergence range and 2) ...
We describe a novel corner tracking system which substantially reduces algorithmic errors, while sti...
No feature-based vision system can work until good features can be identified and tracked from fram...
Cameras can naturally capture sequences of images, or videos, and for computers to understand videos...
This paper presents an efficient camera tracking using prior knowledge of a target scene?3-D object ...
International audienceWe consider the problem of tracking a given set of point features over large s...
We propose a novel approach to tracking objects by low-level line correspondences. In our implementa...
We propose a novel approach to tracking objects by low-level line correspondences. In our implementa...
Long term tracking of an object, given only a single in-stance in an initial frame, remains an open ...
Long term tracking of an object, given only a single instance in an initial frame, remains an open p...
Long term tracking of an object, given only a single instance in an initial frame, remains an open p...
Feature points and object edges are two kinds of primitives which are frequently used in target trac...
Most modern object trackers combine a motion prior with sliding-window detection, using binary class...
Visual tracking of unknown objects in unconstrained video-sequences is extremely challenging due to ...
We present a markerless tracking approach for augmented reality in poorly textured environments. The...
This thesis proposes a robust on-line tracking method by 1) enlarging the convergence range and 2) ...
We describe a novel corner tracking system which substantially reduces algorithmic errors, while sti...
No feature-based vision system can work until good features can be identified and tracked from fram...
Cameras can naturally capture sequences of images, or videos, and for computers to understand videos...
This paper presents an efficient camera tracking using prior knowledge of a target scene?3-D object ...
International audienceWe consider the problem of tracking a given set of point features over large s...