| 摘要 |
A camera (10) produces a sequence of images (12) processed by a point of interest search algorithm (14) that is parameterizable with a detection threshold (τ) such that the number (N) of points of interest detected in the image varies as a function of the threshold level. The characteristic giving the number (N) of detected points of interest as a function of the threshold (τ) is modelled by a square root decreasing exponential function, which is dynamically parameterizable with values linked to the image to be analyzed. The method comprises the steps of: a) determining (18) values of parameterization of the decreasing exponential function for the current image; b) predicting (18), for this current image, an optimum value of the threshold by using the modelled characteristic, parameterized with the values determined at step a); and c) applying (14), for at least one later image, the point of interest search algorithm with the optimum threshold value (τ) computed at step b). |
| 主权项 |
1. A method of detection of points of interest in a digital image of a sequence of images (12) of a scene picked up by a camera (10), this method implementing an point of interest search algorithm (14) that is parameterizable with a detection threshold (τ) such that the number (N) of points of interest detected in the image varies as a function of the threshold level,
this method being characterized by a modeling by a decreasing exponential function of the characteristic giving the number (N) of detected points of interest as a function of the threshold (τ), this exponential function being dynamically parameterizable with values (C, σ) linked to an image to be analysed, and in that it comprises the following steps: a) determining (18), for a current image, values of parameterization (C, σ) of the decreasing exponential function; b) predicting (18), for said current image, an optimum value of the detection threshold (τ) by using the modelled characteristic, parameterized with the values determined at step a); and c) applying (14), for at least one image following said current image, the point of interest search algorithm with the optimum detection threshold value (τ) computed at step b). |
