Stereo Classification and Performance Evaluation

cvlab
|SAD|TAD|SSD|original|

Classification and performance evaluation of different aggregation costs for stereo matching


Preliminary experimental results

This table presents the results obtained by the evaluated algorithms on the Middlebury Dataset [11]. For all the algorithms, the local cost measure adopted is that originally proposed by the authors in their work. For those works not addressing a specific measure, the Sum of Absolute Differences (SAD) was used (for additional results concerning different measures, please refer to the sub-menu on top of this page).
The table allows to interactively explore the results:

All the tuned parameter values for each algorithm which were used to produce the experimental results shown in this table are available here.

NOTE: all variants of algorithm Multiple Windows were implemented withouth the use of incremental schemes (Box-Filtering, Integral Images, ..). Hence the reported processing times concerning that algorithm are higher than those achievable by means of any of such techniques.


Algorithm Rank
Accuracy
Tsukuba
nonocc
Tsukuba
disc
Venus
nonocc
Venus
disc
Teddy
nonocc
Teddy
disc
Cones
nonocc
Cones
disc
Rank
Time
Time Teddy
(hh:mm:ss)
Avg.
Rank
1.00 1 1 1 1 1 1 1 1 12 00:00:37 6.50
3.13 4 4 3 4 4 2 2 2 11 00:00:28 7.06
3.25 2 2 5 3 2 3 5 4 19 00:39:30 11.13
3.50 5 6 2 2 3 4 3 3 8 00:00:15 5.75
5.75 7 7 6 5 5 4 6 6 7 00:00:14 6.38
6.75 3 5 4 7 7 7 11 10 13 00:05:14 9.88
6.88 10 3 11 10 7 5 4 5 18 00:20:35 12.44
7.00 8 8 8 6 6 6 7 7 5 00:00:09 6.00
8.75 9 10 12 8 8 7 8 8 4 00:00:05 6.38
11.13 6 9 7 9 11 8 22 17 10 00:00:26 10.56
11.13 11 13 10 12 13 9 12 9 14 00:13:39 12.56
14.50 14 16 9 14 17 13 18 15 6 00:00:13 10.25
14.88 15 18 16 20 9 17 9 15 3 00:00:04 8.94
15.13 12 20 14 17 12 16 14 16 7 00:00:14 11.06
15.25 13 12 22 19 15 12 17 12 9 00:00:16 12.13
15.63 17 15 15 16 18 14 16 14 3 00:00:04 9.31
16.38 20 25 13 18 14 15 13 13 17 00:20:20 16.69
16.75 18 11 19 13 20 10 23 20 4 00:00:05 10.38
16.88 16 23 17 21 10 19 10 19 2 00:00:02 9.44
17.00 21 24 21 11 16 11 19 13 22 02:08:17 19.50
18.25 19 17 18 22 19 18 15 18 2 00:00:02 10.13
21.00 22 21 26 25 23 20 20 11 21 01:59:09 21.00
21.13 18 22 20 24 21 22 21 21 1 < 1 s 11.06
22.25 25 26 23 15 22 21 24 22 16 00:17:19 19.13
22.50 23 19 24 18 24 23 25 24 15 00:17:00 18.75
23.00 24 14 25 23 25 24 26 23 20 01:06:21 21.50

References

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