a423f284e9
Canonical coordinates prototype, works for Snavely
2014-10-20 14:23:08 +02:00
70b22150fd
Test vector - Cal3Bundle() focal length = 1 !!
2014-10-20 14:21:31 +02:00
821f776118
Wrapper works to some extent
2014-10-20 09:43:32 +02:00
7ebc8e969f
Charts with default constructors
2014-10-20 09:29:45 +02:00
63ae33088e
Some success on the way to autodiff
2014-10-19 23:47:59 +02:00
e71f9edd37
dimension
2014-10-19 23:13:30 +02:00
9a3d2747b8
Type of dimension<T>::value should be int
2014-10-19 23:13:20 +02:00
8ee16c9018
Comments for Paul
2014-10-19 11:19:09 +02:00
eac76cd0f0
Some progress on defining interface
2014-10-19 11:18:36 +02:00
768f47174b
Forgot one is_manifold/dimension
2014-10-19 00:50:33 +02:00
6e142184cc
Implemented is_manifold and dimension for all types in testExpressionFactor
2014-10-19 00:35:25 +02:00
c32d2bb3b2
Fixed comments
2014-10-18 23:48:51 +02:00
d436d99146
Moved stuff to Manifold.h
2014-10-18 23:25:25 +02:00
fcda501ee2
double as manifold. No more LieScalar !
2014-10-18 18:13:33 +02:00
ed6a2b6eff
Charts !!!!
2014-10-18 17:11:28 +02:00
9c97b1d8a0
Some more refactoring
2014-10-18 16:45:04 +02:00
66b3081603
localCoordinates and retract
2014-10-18 15:02:22 +02:00
10cfd47404
TangentVector meta-function
2014-10-18 14:29:40 +02:00
ec69949f43
Point2 specialized
2014-10-18 14:22:01 +02:00
f08dc6c031
More boost-style traits
2014-10-18 14:16:24 +02:00
4c33444415
Snavely tested
2014-10-18 13:16:44 +02:00
bdf12b14b9
Add Snavely cost function
2014-10-18 12:35:02 +02:00
7018afdd58
Slight refactor of numerical derivatives
2014-10-18 12:34:05 +02:00
2972671064
Use boost::bind to avoid code duplication
2014-10-18 12:29:14 +02:00
db037c96c5
Implemented manifold_traits to allow numerical derivatives wrpt Matrix arguments
2014-10-18 12:12:25 +02:00
2cbba15573
ceres style functor
2014-10-18 00:29:18 +02:00
02d25f6658
New tests on traceSize
2014-10-16 15:07:05 +02:00
0bcca2c386
Drastic reduction in allocations at ExpressionFactor construction by having dims constructed imperatively, and using it for both keys_ and dimensions_
2014-10-16 14:16:58 +02:00
944422e295
Only ExpressionFactor needs dimensions! Also, add dimensions at construction -> speeds up linearize.
2014-10-16 11:15:47 +02:00
3413b98331
New storage sizes
2014-10-15 14:30:36 +02:00
5bcc3d922c
Just always store transpose? Problem with optional was that the *empty* optional was copied from the Values, so we gained nothing.
...
However, this is expensive space-wise (double), and optimizes for a particular usage of Rot3, so does not seem good practice (see stack overflow discussion, as well). But the alternative is cumbersome.
2014-10-15 14:28:47 +02:00
c4bf680e96
Cached Rot3::transpose(). Inspired by @cbeall3 fix of Unit3, I realized that with one million points and 1000 cameras, the same Matrix3 (R_.transpose()) was computed a 1000 more times than needed. Especially with quaternions this would be expensive, even with Rot3Q.
2014-10-15 11:51:41 +02:00
4a854f7e22
No using namespace in headers
2014-10-15 11:01:27 +02:00
898c06ccbb
New multi-threaded, realistic SFM example (1M factors, not 1M calls on same factor)
2014-10-15 11:01:02 +02:00
79ff0c54f9
createUnknowns
2014-10-15 10:38:54 +02:00
00d0a7b045
Merge branch 'feature/BAD_stackAb' into feature/BAD
2014-10-15 01:20:01 +02:00
9b1c9bbf37
Allocate temporary matrix on the stack rather tahn on heap, and give VerticalBlockMatrix a view on it.
2014-10-15 00:56:06 +02:00
c88b2a5902
Fixed bizarre link erro as well as off-by-1 bug
2014-10-15 00:34:28 +02:00
0f055f7910
Pass matrix to VerticalBlockMatrix constructor
2014-10-15 00:28:53 +02:00
2092705d12
Allow for other Eigen matrix types
2014-10-15 00:27:43 +02:00
625b939b66
Another very significant speed-up of reverseAD pipeline, by template specialization of the leaf case for fixed matrices. Unfortunately, while this sped up reverse AD for our SFM kernel by 300%, reverseAD was only 6%, and is now 2% of total time. So, time to look elsewhere.
...
Oh, and, it is clear that the Identity matrix for Leaf only expressions is completely known at compile time: Eigen::Matrix<double, T::dimension, T::dimension>::Identity(). That should nicely speed up many a PriorFactor (replacement).
2014-10-14 23:40:21 +02:00
4894dccf5b
Merge branch 'feature/BAD_linearize' into feature/BAD: Now awesome performance!
...
In this I branch essentially implemented two things
1) I used template-meta-programming to automate adding more functional nodes
2) I overloaded "linearize" so that now reverse AD writes to Eigen::Block<Matrix> views of the VerticalBlockMatrix that will be passed to the JacobianFacor. This did wonders for performance, making the AD pipeline faster than dedicated factors. Because the latter is based on optional<Matrix> references, they cannot apply the same trick :-(
3) Finally, I removed the forward AD pipeline. Not worth keeping (this implementation) alive.
2014-10-14 18:05:59 +02:00
baaeaacabe
Made dimensions constant property. Now performance is ***blazing***, way past custom factors.
2014-10-14 17:46:57 +02:00
c971207abf
Switched to vector for dimensions
2014-10-14 17:16:31 +02:00
1c3f328fb2
Successful switch to Blocks !
2014-10-14 15:43:41 +02:00
f3e1561105
Prepare VerticalBlockMatrix for filling
2014-10-14 11:13:49 +02:00
027759300d
size_t argument for check
2014-10-14 11:13:09 +02:00
4c76f39009
Now uses dimensions
2014-10-14 09:55:34 +02:00
d8d94d0c34
dimensions implemented and tested
2014-10-14 09:53:47 +02:00
781cc6daa9
keys now from expression_
2014-10-14 08:59:01 +02:00
dellaert