Abstract: Dot templates are used for detecting objects within images. A computer-implemented method is performed for each of a number of dot templates corresponding to the object to be detected within an image. Each dot template is defined as a collection of points. At each position within the image, a value of the image is determined at each point of the dot template. The dot template is effectively overlaid at the given position within the image. A score of the dot template at this position is determined, based on the values of the image determined at the points of the dot template. Where the score is greater than a predetermined threshold, it can be concluded that the object is at least potentially located within the image at the position in question at which the dot template has been effectively overlaid.

Abstract: Road signs are recognized within field-of-view (FOV) video data having frames. Within a first stage, one or more candidate road signs within the FOV video data are identified, by statically analyzing each frame of the FOV video data independently to detect the one or more candidate road signs within the FOV video data. Within a second stage, each candidate road sign is confirmed or rejected as an actual candidate road sign within the FOV video data by dynamically analyzing the frames of the FOV video data interdependently. The first stage is a static analysis that considers each frame of the FOV video data independently. The second stage is a dynamic analysis that considers the frames of the FOV video data interdependently.