Acta Optica Sinica, Volume. 37, Issue 12, 1215004(2017)
Multi-Scale Stereo Matching Based on Bayesian Reasoning
Figures & Tables(6)
Fig. 1. Flow chart of multi-scale optimization algorithm. (a) Left and right images of binocular vision; (b) disparity maps with scale information; (c) disparity space constructed by disparity maps; (d) histogram of cumulative plausibility of one pixel; (e) final optimization results
Fig. 2. (a) Reference images; disparity maps with different window sizes: (b) window diameter is 1/100 image width; (c) window diameter is 1/50 image width; (d) window diameter is 1/30 image width
Fig. 3. Comparison of experimental results. (a) Ground truth maps; (b) RealTime BP algorithm; (c) FastBilateral algorithm; (d) MSO algorithm; (e)-(g) corresponding mismatched regions
Table 1. Performance comparison of proposed algorithm with other real-time algorithms
View tableTable 1. Performance comparison of proposed algorithm with other real-time algorithms
Algorithm Average Tsukuba Venus Teddy Cones nocc all disc nocc all disc nocc all disc nocc all disc Ref. [20] 9.82 2.05 4.22 10.60 1.92 2.98 20.30 7.23 14.40 17.60 6.41 13.70 16.50 Ref. [23] 9.34 3.19 5.05 9.85 0.57 2.13 5.30 10.60 19.60 22.10 5.52 15.90 12.30 Ref. [19] 7.69 1.49 3.40 7.87 0.77 1.90 9.00 8.72 13.20 17.20 4.61 11.60 12.40 Ref. [31] 7.65 1.71 2.22 6.74 0.55 0.87 2.88 9.90 15.00 19.50 6.66 12.30 13.40 Ref. [32] 7.31 2.38 2.80 10.40 0.34 0.92 4.55 9.83 15.30 20.30 3.10 9.31 8.59 MSO(BM) 5.96 2.31 2.67 9.63 0.32 0.54 2.43 7.87 10.50 16.62 2.87 7.78 8.03
Table 2. Performance comparison of proposed algorithm by using BM algorithm and GF algorithm to create disparity space
View tableTable 2. Performance comparison of proposed algorithm by using BM algorithm and GF algorithm to create disparity space
Algorithm Average Tsukuba Venus Teddy Cones nocc all disc nocc all disc nocc all disc nocc all disc MSO(BM) 5.96 2.31 2.67 9.63 0.32 0.54 2.43 7.87 10.50 16.62 2.87 7.78 8.03 MSO(GF) 5.64 2.34 2.61 8.85 0.31 0.54 2.70 7.53 10.33 15.22 2.58 7.50 7.16
Table 3. Comparison of speed performance of proposed algorithm and other real-time algorithms
View tableTable 3. Comparison of speed performance of proposed algorithm and other real-time algorithms
Algorithm Processor Time /ms MDE per second Ref. [23] 2.5 GHz CPU 8000 0.27* Ref. [19] 3.0 GHz CPU, NVIDAI 7900 GTX 104.9* 17.0 Ref. [32] 2.5 GHz CPU, NVIDAI GTX460 65.5 27.2* Ref. [20] 3.0 GHz CPU, ATI Radeon XL1800 33.6* 52.7 Ref. [31] 2.66 GHz CPU, NVIDAI 8800 GTX 17.5 100.9 MSO(BM) 3.2 GHz CPU, NVIDAI GTX730 15.0 106.1
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Cancan Zeng, Mingjun Ren, Gaobo Xiao, Yuehong Yin. Multi-Scale Stereo Matching Based on Bayesian Reasoning[J]. Acta Optica Sinica, 2017, 37(12): 1215004
Paper Information
Category: Machine Vision
Received: Jun. 30, 2017
Accepted: --
Published Online: Sep. 6, 2018
The Author Email: Ren Mingjun (renmj@sjtu.edu.cn)
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