Method

Object Scene Flow [st] [OSF]
http://www.cvlibs.net/projects/objectsceneflow

Submitted on 14 Nov. 2014 22:07 by
Moritz Menze (Leibniz Universität Hannover)

Running time:50 min
Environment:1 core @ 3.0 Ghz (Matlab + C/C++)

Method Description:
We propose a novel model and dataset for 3D scene flow estimation with an application to autonomous driving. Taking advantage of the fact that outdoor scenes often decompose into a small number of independently moving objects, we represent each element in the scene by its rigid motion parameters and each superpixel by a 3D plane as well as an index to the corresponding object. This minimal representation increases robustness and leads to a discrete-continuous CRF where the data term decomposes into pairwise potentials between superpixels and objects. Moreover, our model intrinsically segments the scene into its constituting dynamic components.
Parameters:
See supplementary material.
Latex Bibtex:
@INPROCEEDINGS{Menze2015CVPR,
author = {Moritz Menze and Andreas Geiger},
title = {Object Scene Flow for Autonomous Vehicles},
booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2015}
}

Detailed Results

This page provides detailed results for the method(s) selected. For each of the first 20 test images, the number of erroneous pixels at all thresholds is depicted in the table. Underneath, the left input image, the disparity / end-point error map and the estimated (and interpolated) disparity / optical flow map are shown. The error map scales linearly between 0 (black) and >=5 (white) pixels error. Red denotes all occluded pixels, falling outside the image boundaries. The false color map is scaled to the largest ground truth disparity / flow value.

Test Set Average

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 5.82 % 9.87 % 1.0 px 1.5 px
3 pixels 3.47 % 6.34 % 1.0 px 1.5 px
4 pixels 2.48 % 4.63 % 1.0 px 1.5 px
5 pixels 1.94 % 3.64 % 1.0 px 1.5 px
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Reflective Regions

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Test Image 0

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 3.16 % 5.50 % 0.6 px 0.8 px
3 pixels 2.15 % 3.36 % 0.6 px 0.8 px
4 pixels 1.63 % 2.64 % 0.6 px 0.8 px
5 pixels 1.06 % 1.99 % 0.6 px 0.8 px
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Test Image 1

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 3.67 % 6.70 % 0.5 px 0.7 px
3 pixels 2.58 % 4.95 % 0.5 px 0.7 px
4 pixels 1.71 % 3.35 % 0.5 px 0.7 px
5 pixels 1.33 % 2.39 % 0.5 px 0.7 px
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Test Image 2

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 3.10 % 7.12 % 0.5 px 0.8 px
3 pixels 1.73 % 4.50 % 0.5 px 0.8 px
4 pixels 1.22 % 3.45 % 0.5 px 0.8 px
5 pixels 0.81 % 2.57 % 0.5 px 0.8 px
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Test Image 3

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 3.83 % 7.54 % 0.6 px 0.9 px
3 pixels 2.04 % 3.58 % 0.6 px 0.9 px
4 pixels 1.31 % 2.63 % 0.6 px 0.9 px
5 pixels 0.84 % 2.07 % 0.6 px 0.9 px
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Test Image 4

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 2.76 % 3.40 % 0.6 px 0.6 px
3 pixels 1.53 % 1.73 % 0.6 px 0.6 px
4 pixels 0.39 % 0.60 % 0.6 px 0.6 px
5 pixels 0.35 % 0.49 % 0.6 px 0.6 px
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Test Image 5

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 5.08 % 12.35 % 0.8 px 1.1 px
3 pixels 2.31 % 6.63 % 0.8 px 1.1 px
4 pixels 1.40 % 3.88 % 0.8 px 1.1 px
5 pixels 1.06 % 2.46 % 0.8 px 1.1 px
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Test Image 6

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 3.52 % 6.97 % 0.5 px 0.8 px
3 pixels 2.25 % 4.18 % 0.5 px 0.8 px
4 pixels 1.68 % 2.36 % 0.5 px 0.8 px
5 pixels 1.43 % 2.00 % 0.5 px 0.8 px
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Test Image 7

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 6.26 % 8.23 % 1.0 px 1.4 px
3 pixels 4.17 % 5.11 % 1.0 px 1.4 px
4 pixels 3.11 % 3.80 % 1.0 px 1.4 px
5 pixels 2.66 % 3.17 % 1.0 px 1.4 px
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Test Image 8

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 4.58 % 9.35 % 0.7 px 1.0 px
3 pixels 2.62 % 5.19 % 0.7 px 1.0 px
4 pixels 1.66 % 2.95 % 0.7 px 1.0 px
5 pixels 1.27 % 1.97 % 0.7 px 1.0 px
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Test Image 9

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 8.79 % 15.28 % 1.3 px 2.2 px
3 pixels 4.66 % 9.70 % 1.3 px 2.2 px
4 pixels 3.64 % 8.03 % 1.3 px 2.2 px
5 pixels 3.21 % 6.92 % 1.3 px 2.2 px
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Test Image 10

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 6.34 % 12.60 % 0.7 px 1.1 px
3 pixels 3.17 % 7.92 % 0.7 px 1.1 px
4 pixels 1.88 % 5.68 % 0.7 px 1.1 px
5 pixels 1.22 % 3.96 % 0.7 px 1.1 px
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Test Image 11

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 5.49 % 8.52 % 0.9 px 1.2 px
3 pixels 2.70 % 4.38 % 0.9 px 1.2 px
4 pixels 1.84 % 3.27 % 0.9 px 1.2 px
5 pixels 1.56 % 2.85 % 0.9 px 1.2 px
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Test Image 12

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 5.61 % 10.64 % 1.1 px 1.6 px
3 pixels 4.01 % 7.43 % 1.1 px 1.6 px
4 pixels 3.16 % 5.89 % 1.1 px 1.6 px
5 pixels 2.76 % 5.03 % 1.1 px 1.6 px
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Test Image 13

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 2.97 % 5.92 % 0.7 px 1.1 px
3 pixels 2.15 % 4.62 % 0.7 px 1.1 px
4 pixels 1.82 % 4.02 % 0.7 px 1.1 px
5 pixels 1.66 % 3.71 % 0.7 px 1.1 px
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Test Image 14

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 4.06 % 7.99 % 0.6 px 0.8 px
3 pixels 1.95 % 4.43 % 0.6 px 0.8 px
4 pixels 1.01 % 2.61 % 0.6 px 0.8 px
5 pixels 0.74 % 1.74 % 0.6 px 0.8 px
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Test Image 15

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 7.42 % 12.90 % 1.0 px 1.6 px
3 pixels 4.84 % 8.90 % 1.0 px 1.6 px
4 pixels 3.65 % 6.74 % 1.0 px 1.6 px
5 pixels 2.78 % 5.21 % 1.0 px 1.6 px
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Test Image 16

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 1.25 % 2.54 % 0.4 px 0.5 px
3 pixels 0.72 % 1.20 % 0.4 px 0.5 px
4 pixels 0.52 % 0.75 % 0.4 px 0.5 px
5 pixels 0.37 % 0.54 % 0.4 px 0.5 px
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Test Image 17

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 7.16 % 11.28 % 0.9 px 1.6 px
3 pixels 5.21 % 8.55 % 0.9 px 1.6 px
4 pixels 4.27 % 7.17 % 0.9 px 1.6 px
5 pixels 3.70 % 6.27 % 0.9 px 1.6 px
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Test Image 18

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 4.41 % 4.80 % 0.6 px 0.6 px
3 pixels 2.83 % 2.63 % 0.6 px 0.6 px
4 pixels 1.90 % 1.77 % 0.6 px 0.6 px
5 pixels 1.01 % 0.96 % 0.6 px 0.6 px
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Test Image 19

Error Out-Noc Out-All Avg-Noc Avg-All
2 pixels 1.31 % 2.41 % 0.4 px 0.6 px
3 pixels 0.62 % 1.08 % 0.4 px 0.6 px
4 pixels 0.42 % 0.73 % 0.4 px 0.6 px
5 pixels 0.32 % 0.51 % 0.4 px 0.6 px
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