Opto-Electronic Engineering, Volume. 51, Issue 10, 240166(2024)
Unsupervised light field depth estimation based on sub-light field occlusion fusion
Figures & Tables(13)
Fig. 1. Illustrations of center view and warping errors of left,right,top,and bottom views. (a) Center view; (b) Warping error of left view; (c) Warping error of right view; (d) Warping error of top view; (e) Warping error of bottom view
Fig. 2. Sub-light field division and spatial and angular flip ( 3×3 as an example)
Fig. 5. Comparison of depths and bad pixel maps estimated by different methods on Boxes from the HCI new dataset [19]
Fig. 6. Comparison of depths and bad pixel maps estimated by different methods on Pyramids from the HCI new dataset [19]
Fig. 7. Comparison of depths and bad pixel maps estimated by different methods on Pinenuts from the DLF dataset [20]
Fig. 8. Comparison of depths and bad pixel maps estimated by different methods on Toys from the DLF dataset [20]
Fig. 9. Comparison of depths estimated by different methods on real-world data from the Stanford Lytro dataset [23]
Table 1. Quantitative comparison of different light field depth estimation methods in terms of MSE (×100) (bolded indicates first,underlined indicates second)
View tableView in ArticleTable 1. Quantitative comparison of different light field depth estimation methods in terms of MSE (×100) (bolded indicates first,underlined indicates second)
Type Methods Boxes Cotton Pyramids Sideboard Antiques Pinenuts Smiling Toys Ave. Tradi- tional OCC [ 6 ]12.22 9.47 1.81 18.76 38.76 46.95 237.26 10.49 46.97 SPO [ 7 ]9.57 1.99 0.20 1.34 3.00 1.32 6.53 0.90 3.11 OAVC [ 8 ]7.46 1.47 0.08 1.55 5.38 1.62 4.77 1.02 2.92 Unsup- ervised Unsup [ 13 ]12.21 7.37 0.43 3.82 11.87 30.69 17.68 2.38 10.81 OccUnNet [ 15 ]6.94 1.68 0.17 7.54 3.23 19.04 4.93 0.70 5.53 Proposed 6.61 2.22 0.04 2.07 4.10 0.70 4.80 0.67 2.65
Table 2. Quantitative comparison of different light field depth estimation methods in terms of BPR (>0.07) (bolded indicates first,underlined indicates second)
View tableView in ArticleTable 2. Quantitative comparison of different light field depth estimation methods in terms of BPR (>0.07) (bolded indicates first,underlined indicates second)
Type Methods Boxes Cotton Pyramids Sideboard Antiques Pinenuts Smiling Toys Ave. Tradi- tional OCC [ 6 ]40.05 46.39 12.17 48.81 72.53 62.81 71.03 83.33 54.64 SPO [ 7 ]42.58 29.79 14.87 32.32 31.63 40.07 18.93 41.51 31.46 OAVC [ 8 ]18.59 5.19 2.91 19.59 6.71 11.40 23.13 10.17 12.21 Unsup- ervised Unsup [ 13 ]43.75 23.97 14.75 26.37 33.43 48.94 42.45 29.50 32.90 OccUnNet [ 15 ]27.39 7.03 6.41 17.50 17.57 43.58 21.77 16.52 19.72 Proposed 24.70 6.39 0.78 16.26 9.32 29.95 15.63 10.64 14.21
Table 3. Quantitative comparison of different light field depth estimation methods in terms of runtime (s),where traditional methods run on CPU and unsupervised methods run on GPU (bolded indicates first,underlined indicates second)
View tableView in ArticleTable 3. Quantitative comparison of different light field depth estimation methods in terms of runtime (s),where traditional methods run on CPU and unsupervised methods run on GPU (bolded indicates first,underlined indicates second)
Type Methods Boxes Cotton Pyramids Sideboard Antiques Pinenuts Smiling Toys Ave. Tradi- tional OCC [ 6 ]192.05 210.73 319.46 222.10 205.32 172.03 242.53 166.85 216.38 SPO [ 7 ]831.91 820.72 790.02 814.70 794.63 807.51 803.15 807.74 808.80 OAVC [ 8 ]16.33 16.60 16.50 16.47 16.62 16.74 16.62 16.72 16.58 Unsup- ervised Unsup [ 13 ]39.38 39.14 39.55 39.49 39.72 39.47 39.21 38.38 39.29 OccUnNet [ 15 ]0.24 0.24 0.24 0.24 0.24 0.24 0.24 0.24 0.24 Proposed 0.01 0.01 0.01 0.02 0.01 0.01 0.01 0.01 0.01
Table 4. Results of ablation experiment
View tableView in ArticleTable 4. Results of ablation experiment
Schemes MSE(×100) BPR(>0.07) Scheme 1 5.85 15.23 Scheme 2 2.74 17.34 Scheme 3 3.04 20.52 Scheme 4 3.54 20.88 Scheme 5 3.74 18.16 Scheme 6 4.02 18.98 Scheme 7 2.89 21.60 Scheme 8 2.75 16.24 Scheme 9 2.89 18.32 Proposed 2.65 14.21
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Haoyu Li, Yeyao Chen, Zhidi Jiang, Gangyi Jiang, Mei Yu. Unsupervised light field depth estimation based on sub-light field occlusion fusion[J]. Opto-Electronic Engineering, 2024, 51(10): 240166
Paper Information
Category: Article
Received: Jul. 15, 2024
Accepted: Sep. 10, 2024
Published Online: Jan. 2, 2025
The Author Email: Mei Yu (郁梅)
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