|| || || || || ||

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Todo List

Member Impala::Core::Training::ApplyConceptsHelperKernels::Predict (const ModelLocator &loc)

perhaps we can use the code in SvmHelper?

Member Impala::Core::Tracking::Classifier::MultiplyWithTranspose (Array::Array2dScalarReal64 *&matrix, const Array::Array2dScalarReal64 *vector)

should move to Core/Matrix

Member Impala::Core::Tracking::Classifier::MultiplyWithTranspose (Array::Array2dScalarReal64 *&matrix, const double *vec)

should move to Core/Matrix

Member Impala::Core::Tracking::Classifier::AddMatrixWeighted (Array::Array2dScalarReal64 *&matrix, const Array::Array2dScalarReal64 *addmatrix, double weight)

should move to Core/Matrix

Member Impala::Core::Tracking::Classifier::MeanFromSamples (Array::Array2dScalarReal64 *&mean, const Array::Array2dScalarReal64 *samples)

should move to Core/Matrix

Member Impala::Core::Tracking::Classifier::SommateTransposeMultiplications (Array::Array2dScalarReal64 *&matrix, const Array::Array2dScalarReal64 *samples)

should move to Core/Matrix, except relies on mDimensionality

Member Impala::Core::Tracking::Classifier::CrossProduct (const Array::Array2dScalarReal64 *vector1, const Array::Array2dScalarReal64 *vector2)

should move to Core/Matrix

Class Impala::Core::Table::CriterionElement1InSet< T >

make a faster implementation, this one's O(n^2), can at least be O(n*log(n)), can be O(n) when both tables are sorted

Member Impala::Core::Training::Factory::MakeImage (Quid q)

check that this is really the idiomatic way to get an image

Member Impala::Core::Array::Trait::FuncKalman::doIt (const Vec3Real64 &p1, const Vec3Real64 &p2, int x, int y)

check correctness of outliers during occlusion

Member Impala::Core::Array::Trait::InOutSetRandom::DoIt ()

change implementation

Class Impala::Core::VideoSet::LbpEval

refactor this -> LpbEval should be split, there is duplication of code in ProtoSimilarityEval. Make a baseclass for Feature::Computor and derive an Lbp computor thereof.

Member Impala::Visualization::Plot::Plottable::Draw (Plot *plot)=0

decide what coordinate system to draw in, for now assume [-1..1] in all dimensions

Class Impala::Core::Training::Svm

Fix the machanism to set gamma to 1/vectorlength. See OverrideModelOptions(), Train() and MakeSvmParams().

Member Impala::Core::Training::SvmProblemBuilder::AddFeatureTable (Feature::FeatureTable *table)

We can speed things up by assuming everything is sorted on quids, in that case we don't have to search the QuidTable with GetIndex

Class Impala::Core::Tracking::TrackerBackFore

add parameters (such as sigma, number of orientations) to constructor (perhaps in struct)

Member Impala::Core::Tracking::TrackerBackFore::FillSearchArea (Array::Array2dVec3Real64 *searchArea, int bw, int bh)

PatSet in such a way the border is filled with a part of the image in stead of this ugly hack

Member Impala::Core::Tracking::TrackerGeneralised::Clip (Position &pos)

take rotation and scale into consideration.

Class Impala::Core::Training::TrainDataSrc

Ideally this class should be independant of the Classifier used. Perhaps the MakeSvmProblem will be replaced with an interface to the vectors, and labels of individual samples.

Class Impala::Core::Training::TrainDataSrc

The function free problem does not belong in this class. In stead of a funcitno like this, svm_problem should have a wrapper so the destructor can take care of this.

Member Impala::Application::Precompute::GetPartial (Feature::FeatureTable *f, int partnumber, int partcount)

find better name

Member Impala::Core::Array::InvQuasi (Array2dVec3Real64 *src, double sigma, double precision)

perhaps this function should be split in 3 functions that compute the quasi invariant and variant for the three categories...

Member Impala::Core::Vector::Apply (double(*fn)(const VectorTem< double > &, const VectorTem< double > &), const VectorSet< Array::Array2dScalarReal64 > *horizontal, const VectorSet< Array::Array2dScalarReal64 > *vertical)

apply to pattern coding style, introduce function object i.s.o. function pointer

Member Impala::Core::Vector::HistogramAccumulation (VectorSet< ArrayT > *vs, bool doNormalizeHeight, bool doNormalizeWeight, bool *filter)

: the name is not correct??

Member Impala::Util::Broadcast (IOBuffer *buffer, int root)

investigate performance of MPI vs, Franks implementations

Namespace OglGui

XXX RvB: apart from SetAllowSizeDirection, also implement function to disable a certain direction, leaving other settings alone: SetDisableSizeDirection. Same goes for move: SetDisableMoveDirection. Or alternatively add a flag to SetAllowSizeDirection(dir, bool mode) latter method is preferred

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