¸ 057 058 059 060 061 062 063 064 065 066 067 068 069 070 071 072 073 074 075 076 077 078 079 080 081 082 083 084 085 086 087 088 089 090 091 092 093 094 095 096 097 098 099 100 101 102 103 104 cv 106 107 (a) (b) Figure 1: Translational symmetry detection using our method on a typical facade image: (a) Detected symmetry ¸ lattice on input image; (b) Segmented symmetry shapes. Although a number of methods for detecting dissimilar symmetries were developed in the past few decades (refer to [17] for a arrogant survey), goody automatic and robust detecti on of translational symmetry in real-world a! rchitectural images is still a challenging task. In particular, our study during underdeveloped an image-based facade modeling system ¸ reveals that exist algorithms for symmetry detection in images do not consider our requirements. The reasons are as follows. 1. Symmetry region extraction. Most lively methods only tender results for each feature point or a jittery region. The...If you want to get a full essay, order it on our website: BestEssayCheap.com
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