Stereo Matching Based on Convolutional Neural Network

Fig. 5. Disparity map of stereo matching obtained by proposed method (Ⅰ). (a) Original left input image; (b) original right input image; (c) disparity map; (d) ground truth; (e) error graph

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Fig. 6. Disparity map of stereo matching obtained by proposed method (Ⅱ). (a) Original left input image; (b) original right input image; (c) disparity map; (d) ground truth; (e) error graph

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Table 1. Error comparison for the improvement of loss function%
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Table 1. Error comparison for the improvement of loss function%
Method KITTI2012 KITTI2015 KITTI2012 on KITTI2015 KITTI2015 on KITTI2012
Original loss 2.63 3.28 4.03 3.92
Proposed loss 2.61 3.25 4.02 3.89

Table 2. Error comparison between different Δ values%
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Table 2. Error comparison between different Δ values%
Δ Error
0.02 3.261
0.04 3.266
0.05 3.252
0.06 3.284
0.08 3.267

Table 3. [in Chinese]
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Table 3. [in Chinese]
Training set KITTI2012 KITTI2015
MC-CNN-slow Proposed MC-CNN-slow Proposed
KITTI2012 2.63 2.61 4.01 4.02
KITTI2015 4.32 3.89 3.27 3.25

Table 4. Error comparison of disparity with different algorithms (KITTI2012)%

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Table 4. Error comparison of disparity with different algorithms (KITTI2012)%

Algorithm	>2 pixel	>3 pixel	>4 pixel	>5 pixel
Elas	22.72	21.07	20.23	19.66
SGM	6.28	4.98	4.14	3.57
SPSS	4.86	3.79	3.17	2.76
Fast CNN	4.98	3.07	2.39	2.03
MC-CNN-fast	4.88	3.03	2.30	1.93
MC-CNN-slow	4.28	.63	2.02	1.72
Proposed	4.36	2.61	2.00	1.70

Table 5. Error comparison of disparity with different algorithms (KITTI2015)%

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Table 5. Error comparison of disparity with different algorithms (KITTI2015)%

Algorithm	>2 pixel	>3 pixel	>4 pixel	>5 pixel
Elas	24.09	19.21	17.59	16.82
SGM	10.03	6.93	5.47	4.48
SPSS	7.15	4.58	3.46	2.93
Fast CNN	6.78	4.38	2.56	2.03
MC-CNN-fast	7.53	4.01	2.84	2.33
MC-CNN-slow	6.38	3.27	2.37	1.97
Proposed	6.56	3.25	2.33	1.92

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Jinsheng Xiao, Hong Tian, Wentao Zou, Le Tong, Junfeng Lei. Stereo Matching Based on Convolutional Neural Network[J]. Acta Optica Sinica, 2018, 38(8): 0815017

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