Optical Flow Measurement Based on Boolean Edge Detection and Hough Transform |
Chang, Min-Hyuk
(Division of Electronics and Information and Communication Engineering, Chosun University)
Kim, Il-Jung (Division of Electronics and Information and Communication Engineering, Chosun University) Park, Jong an (Division of Electronics and Information and Communication Engineering, Chosun University) |
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Multiconstraints-based optical flow estimation and segmentation
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2 |
Combining motion and contrast for segmentation
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3 |
Stochastic relaxation, Gibbs distribution, and Bayesian restoration of images
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4 |
Combining intensity and motion for incremental segmentation and tracking over long image sequence
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5 |
Tracking moving objects in television images
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DOI ScienceOn |
6 |
Object tracking with a moving camera
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7 |
Segmentation and 2D motion estimate by region fragments
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8 |
Estimation of moving information for tracking of moving objects
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A combinatorial Hough transform
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DOI ScienceOn |
10 |
Local threshold and Boolean function based edge detection
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DOI ScienceOn |
11 |
Displacement vectors derived from second-order intensity variations in image sequences
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DOI ScienceOn |
12 |
Computing optical flow from an overconstrained system of linear algebraic equations
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13 |
On the information in optical flow
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DOI ScienceOn |
14 |
Obstacle avoidance using field divergence
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DOI ScienceOn |
15 |
Bounds on time-to-collision and rotation component from first-order derivatives of image flow
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DOI ScienceOn |
16 |
Determining optical flow
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DOI ScienceOn |
17 |
Towards the estimation of displacement vector fields by 'oriented smoothness' constraints
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