Abstract: Object detection receives an input image to detect an object of interest. It determines feature matrices based on the received image, wherein each matrix represents a feature of the received image. The plurality of matrices are Fourier transformed to Fourier feature matrices. Fourier filter matrices are provided, each representing a feature of an object transformed in Fourier space. Each filter matrix is point-wise multiplied with one of the feature matrices corresponding to the same feature. The plurality of matrices are summed, resulting by point-wise multiplying each Fourier filter matrix with the corresponding Fourier feature matrix to obtain a Fourier score matrix. An inverse Fourier transform of the Fourier score matrix is performed, resulting in a score matrix, which is used to detect the object in the input image.

Abstract: The present invention discloses a method, apparatus and computer program product for determining the location of a plurality of speech sources in an area of interest, comprising performing an algorithm on a signal issued by either one of said plurality of speech sources in the area to for iteratively recover data characteristic to said signal, wherein the algorithm is an iterative model-based sparse recovery algorithm, and wherein for each of a plurality of points in said area, the iteratively recovered data is indicative of a presence of a plurality of speech sources contributing to the signal received at each of a plurality of points in the area.