A computer-implemented method of using semantic object characterizations to index a database directory, said method comprising: inputting pairs of parallel semantic objects, wherein a pair of parallel semantic objects comprises the same semantic object presented in first and second representations or views; subjecting each semantic object in each pair of parallel semantic objects to feature extraction to produce a feature vector representing the semantic object; the method being characterized by: employing a correlation and optimization method to establish a prescribed number of transforms for the first representation or view and the same number of transforms for the second representation or view based on the feature vectors representing the parallel semantic object pairs, wherein the transforms established for one of the first or second representations or views, when applied to a feature vector representing a semantic object exhibiting that representation or view, produce a first binary hash code representing that semantic object which exhibits a prescribed degree of similarity to a second binary hash code representing that semantic object produced when the transforms established for the other of the first or second representations or views are applied to a feature vector representing the same semantic object exhibiting that other representation or view, and wherein said transforms established for the first representation or view are not all the same as the transforms established for the second representation or view; using the transforms established for the first representation or view to characterize a semantic object exhibiting the first representation or view as the first binary hash code representing that semantic object; and associating the first binary hash code representing that semantic object with its corresponding semantic object in the database directory. inputting pairs of parallel semantic objects, wherein a pair of parallel semantic objects comprises the same semantic object presented in first and second representations or views; subjecting each semantic object in each pair of parallel semantic objects to feature extraction to produce a feature vector representing the semantic object; the method being characterized by: employing a correlation and optimization method to establish a prescribed number of transforms for the first representation or view and the same number of transforms for the second representation or view based on the feature vectors representing the parallel semantic object pairs, wherein the transforms established for one of the first or second representations or views, when applied to a feature vector representing a semantic object exhibiting that representation or view, produce a first binary hash code representing that semantic object which exhibits a prescribed degree of similarity to a second binary hash code representing that semantic object produced when the transforms established for the other of the first or second representations or views are applied to a feature vector representing the same semantic object exhibiting that other representation or view, and wherein said transforms established for the first representation or view are not all the same as the transforms established for the second representation or view; using the transforms established for the first representation or view to characterize a semantic object exhibiting the first representation or view as the first binary hash code representing that semantic object; and associating the first binary hash code representing that semantic object with its corresponding semantic object in the database directory. employing a correlation and optimization method to establish a prescribed number of transforms for the first representation or view and the same number of transforms for the second representation or view based on the feature vectors representing the parallel semantic object pairs, wherein the transforms established for one of the first or second representations or views, when applied to a feature vector representing a semantic object exhibiting that representation or view, produce a first binary hash code representing that semantic object which exhibits a prescribed degree of similarity to a second binary hash code representing that semantic object produced when the transforms established for the other of the first or second representations or views are applied to a feature vector representing the same semantic object exhibiting that other representation or view, and wherein said transforms established for the first representation or view are not all the same as the transforms established for the second representation or view; using the transforms established for the first representation or view to characterize a semantic object exhibiting the first representation or view as the first binary hash code representing that semantic object; and associating the first binary hash code representing that semantic object with its corresponding semantic object in the database directory.