Transitive Closure Based Visual Words for Point Matching in Video Sequence

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.