Matching Image Sequences using Mathematical Programming: Visual Localization Applications

Authors : Abdul Hafiz ABDULHAFIZ

Pages : 1-14

View : 13 | Download : 6

Publication Date : 2020-06-03

Article Type : Research Paper

Abstract :This paper proposes a new visual localization algorithm that utilizes the visual route map to localize the agent. The sequence of the current and past images is matched to the map, i.e. the reference image sequence, to produce the best match of the current image. The image sequence matching is achieved by measuring the similarity between the two image sequences using the dynamic time warping insert ignore into journalissuearticles values(DTW); algorithm. The DTW algorithm employs Dynamic Programming insert ignore into journalissuearticles values(DP); to calculate the distance insert ignore into journalissuearticles values(the cost function); between the two image sequences. Consequently, the output of the alignment process is an optimal match of each image in the current image sequence to an image in the reference one. Our proposed DTW matching algorithm is suitable to be used with a wide variety of engineered features, they are SIFT, HOG, LDP in particular. The proposed DTW algorithm is compared to other recognition algorithms like Support Vector Machine insert ignore into journalissuearticles values(SVM); and Binary- appearance Loop-closure insert ignore into journalissuearticles values(ABLE); algorithm. The datasets used in the experiments are challenging and benchmarks, they are commonly used in the literature of the visual localization. These datasets are the” Garden point”, “St. Lucia”, and “Nordland”. The experimental observations have proven that the proposed technique can significantly improve the performance of all the used descriptors, i.e, SIFT, HOG, and LDB as compared to its individual performance. In addition, it was able to the SVM and ABLE localization algorithm.
Keywords : Dynamic programming, Dynamic time warping, Visual localization