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Monocular SLAM and Real-Time Scene Perception
Published on Oct 09, 201215470 Views
We have seen great advances in real-time 3D vision in recent years, enabled by algorithmic improvements, the continuing increase in commodity processing power and better camera technology. Research in
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Chapter list
Monocular SLAM and Real-Time Scene Perception00:00
Robot Vision00:30
Simultaneous Localisation and Mapping (1)02:43
Simultaneous Localisation and Mapping (2)04:11
Simultaneous Localisation and Mapping (3)04:14
Simultaneous Localisation and Mapping (4)04:16
Simultaneous Localisation and Mapping (5)04:17
Simultaneous Localisation and Mapping (6)04:19
SLAM with First Order Uncertainy Propagation04:46
SLAM Using Vision: First Steps05:50
SLAM Using Active Stereo Vision06:39
Monocular SLAM07:05
MonoSLAM10:22
Application: HRP-2 Humanoid at JRL, AIST, Japan14:46
HRP2 Loop Closure15:10
Application: Wearable Robot SLAM16:16
General Components of a Scalable SLAM System17:04
SLAM as a Bayesian Network18:59
PTAM: Parallel Tracking and Mapping20:09
Real-Time Monocular SLAM: Why Filter?21:24
Double Window Optimisation for Constant Time Visual SLAM24:27
Towards Live Dense Reconstruction26:41
Solving Inverse Problems with Variational Optimisation29:52
GPGPU Processing Power32:45
Live Dense Reconstruction with a Single Camera34:07
Spherical Mosaicing using Whole Image Alignment38:03
DTAM: Dense Tracking and Mapping39:39
Cost volume data term40:35
Using all possible frames from the live camera40:52
Tracking using the dense model40:54
Why Not Increase Frame-Rate to Track Even Faster Motion?43:00
Scalable Active Matching45:12
Experimental Investigation with `Photo-Realistic' Video45:21
Experiment assuming perfect lighting47:56
Moderate lighting49:23
Real-Time Dense Surface Mapping and Tracking49:52
Signed Distance Function surface representations51:20
SDF Fusion (1)52:19
SDF Fusion (2)52:46
SDF Fusion (3)52:48
SDF Fusion (4)52:50
Real-time Surface Fusion using a Single RGB Camera57:44
Towards Greater Physical Understanding58:52