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We present Transitive Closure based visual word formation technique for obtaining robust object representations from smoothly varying multiple views. Each one of our visual words is represented by a set of feature vectors which is obtained by performing transitive closure operation on SIFT features. We also present range-reducing tree structure to speed up the transitive closure operation. The robustness of our visual word representation is demonstrated for Structure from Motion (SfM) and location identification in video images.