11. An apparatus comprising: at least one processor; and a memory in communication with the at least one processor, the memory including non-transitory computer-readable code which, when executed, cause the at least one processor to at least: apply a saliency analysis and segmentation of selected regions in a selected video frame to determine segmented likely logo regions; process the segmented likely logo regions with feature matching using correlation to generate a first match, neural network classification using a convolutional neural network to generate a second match, and text recognition using character segmentation and string matching to generate a third match; and decide a most likely logo match by combining results from the first match, the second match, and the third match.
11. An apparatus comprising: at least one processor; and a memory in communication with the at least one processor, the memory including non-transitory computer-readable code which, when executed, cause the at least one processor to at least: apply a saliency analysis and segmentation of selected regions in a selected video frame to determine segmented likely logo regions; process the segmented likely logo regions with feature matching using correlation to generate a first match, neural network classification using a convolutional neural network to generate a second match, and text recognition using character segmentation and string matching to generate a third match; and decide a most likely logo match by combining results from the first match, the second match, and the third match. 13. The apparatus of claim 11 , wherein saliency detection comprises: applying a discrete cosine transform (DCT) on the segmented likely logo regions of an image in a selected video frame to determine spectral saliency of each likely logo region; and measuring multi-scale similarity at two higher scales and a smaller scale of the spectral saliency of each likely logo region.