Dense Stereo Matching Algorithm Based on Image Segmentation

Ruihao Ma; Feng Zhu; Qingxiao Wu; Rongrong Lu; Jingyang Wei

doi:10.3788/AOS201939.0315001

Acta Optica Sinica, Volume. 39, Issue 3, 0315001(2019)

Dense Stereo Matching Algorithm Based on Image Segmentation

Ruihao Ma^1,2,3, Feng Zhu^1,3、*, Qingxiao Wu^1,3, Rongrong Lu^1,3, and Jingyang Wei^1,3

Author Affiliations

¹ Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China

² College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, China

³ Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China

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Abstract Get PDF(in Chinese)

Figures & Tables(8)

Fig. 1. Flow chart of algorithm. (a) Matching cost aggregation; (b) disparity post-processing; (c) integrated flow chart

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Fig. 2. Result of SLIC algorithm. (a) Tsukuba image; (b) superpixel segmentation image; (c) edge image

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Fig. 3. Results of different algorithms. (a) Hole filling; (b) cross adaptive window weighted median filtering

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Fig. 4. Support region

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Fig. 5. Influences of parameters on AvgPBM. (a) N; (b) β and γ; (c) ρ; (d) T

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Fig. 6. Experimental results. (a) Left image; (b) ground-truth disparity; (c) result of proposed algorithm; (d) result of MST algorithm; (e) result of GF algorithm; (f) result of GA-DP algorithm

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Table 1. AvgPBM for different algorithms%

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Table 1. AvgPBM for different algorithms%

Algorithm	Tsukuba			Venus			Teddy			Cones			Avg PBM	Avg Disc
Algorithm	n-occ	all	disc	n-occ	all	disc	n-occ	all	disc	n-occ	all	disc	Avg PBM	Avg Disc
Proposed	1.50	1.95	6.71	0.11	0.33	1.25	5.27	10.8	14.5	2.38	8.02	7.01	4.99	7.36
MST	1.47	1.85	7.88	0.25	0.42	2.60	6.01	11.6	14.3	2.87	8.45	8.10	5.48	8.08
GF	1.51	1.85	7.61	0.20	0.93	2.42	6.16	11.8	16.0	2.71	8.24	7.66	5.55	8.42
GA-DP	1.57	2.00	7.32	0.89	1.00	3.18	7.20	12.4	16.1	3.68	9.18	8.62	6.10	8.80
Gray	1.91	2.74	9.70	0.32	0.68	4.25	5.99	11.7	16.2	3.70	9.64	10.7	6.46	10.21

Table 2. AvgPBM for different algorithms on n-occ region%

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Table 2. AvgPBM for different algorithms on n-occ region%

Stereo pair	Proposed	GF	CS-MST	Gray	MST
Tsukuba	1.50₂	1.51₃	2.12₅	1.91₄	1.47₁
Venus	0.11₁	0.20₂	0.84₅	0.32₄	0.25₃
Teddy	5.27₁	6.16₅	7.61₄	5.99₃	5.53₂
Cones	2.38₁	2.71₂	4.10₄	3.70₃	6.01₅
Alone	4.58₂	5.53₄	4.14₁	7.13₅	4.63₃
Art	7.08₁	9.03₂	9.79₃	9.88₄	10.79₅
Baby1	2.62₁	4.69₃	7.37₄	3.24₂	8.39₅
Baby2	3.30₁	6.08₃	11.95₄	4.91₂	13.37₅
Baby3	3.46₁	5.79₄	5.64₃	4.52₂	7.25₅
Books	8.29₁	10.22₃	9.56₂	10.64₅	10.26₄
Bowling1	6.48₁	14.52₃	16.81₄	9.77₂	20.89₅
Bowling2	4.87₁	7.08₃	9.31₄	6.82₂	10.15₅
Cloth1	1.01₃	1.08₄	0.51₁	1.12₅	0.61₂
Cloth2	2.31₁	3.46₃	2.85₂	3.57₄	4.13₅
Cloth3	1.46₁	2.15₃	1.77₂	2.20₄	2.66₅
Cloth4	3.20₄	1.62₂	1.30₁	3.74₅	1.87₃
Dolls	4.08₁	5.04₃	5.00₂	6.57₅	5.95₄
Flowerpots	9.80₁	12.79₂	16.67₄	12.88₃	19.41₅
Lampshade1	5.59₁	11.57₄	10.43₃	6.74₂	11.99₅
Lampshade2	13.88₁	21.13₅	20.88₄	15.04₂	18.20₃
Laundry	15.65₃	16.40₄	13.69₂	18.50₅	12.94₁
Midd1	40.10₄	40.11₅	32.32₂	36.67₃	27.85₁
Midd2	39.24₅	35.85₃	34.50₂	36.93₄	32.09₁
Moebius	7.44₁	9.25₄	7.67₂	9.33₅	8.69₃
Monopoly	25.40₃	27.99₅	22.51₁	27.71₄	24.21₂
Plastic	33.62₁	39.29₂	42.53₄	40.21₃	47.03₅
Reindeer	27.57₄	7.23₁	9.15₂	28.36₅	9.87₃
Rocks1	3.68₄	2.70₂	2.23₁	4.41₅	2.83₃
Rocks2	2.04₃	1.61₂	1.57₁	2.58₅	2.08₄
Wood1	3.77₂	2.83₁	8.68₄	4.73₃	11.06₅
Wood2	2.27₂	2.34₃	0.99₁	3.00₄	5.61₅
AvgErr	9.42	10.25	10.44	10.74	11.23
AvgRank	1.87	3.06	2.61	3.67	3.65

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Ruihao Ma, Feng Zhu, Qingxiao Wu, Rongrong Lu, Jingyang Wei. Dense Stereo Matching Algorithm Based on Image Segmentation[J]. Acta Optica Sinica, 2019, 39(3): 0315001

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Paper Information

Category: Machine Vision

Received: Sep. 13, 2018

Accepted: Oct. 21, 2018

Published Online: May. 10, 2019

The Author Email:

DOI:10.3788/AOS201939.0315001

Topics

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