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Diffstat (limited to 'extern/libmv/third_party/ceres/internal/ceres/canonical_views_clustering.h')
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1 files changed, 0 insertions, 136 deletions
diff --git a/extern/libmv/third_party/ceres/internal/ceres/canonical_views_clustering.h b/extern/libmv/third_party/ceres/internal/ceres/canonical_views_clustering.h deleted file mode 100644 index d3fa5725831..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/canonical_views_clustering.h +++ /dev/null @@ -1,136 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2010, 2011, 2012 Google Inc. All rights reserved. -// http://code.google.com/p/ceres-solver/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) -// -// An implementation of the Canonical Views clustering algorithm from -// "Scene Summarization for Online Image Collections", Ian Simon, Noah -// Snavely, Steven M. Seitz, ICCV 2007. -// -// More details can be found at -// http://grail.cs.washington.edu/projects/canonview/ -// -// Ceres uses this algorithm to perform view clustering for -// constructing visibility based preconditioners. - -#ifndef CERES_INTERNAL_CANONICAL_VIEWS_CLUSTERING_H_ -#define CERES_INTERNAL_CANONICAL_VIEWS_CLUSTERING_H_ - -// This include must come before any #ifndef check on Ceres compile options. -#include "ceres/internal/port.h" - -#ifndef CERES_NO_SUITESPARSE - -#include <vector> - -#include "ceres/collections_port.h" -#include "ceres/graph.h" - -namespace ceres { -namespace internal { - -struct CanonicalViewsClusteringOptions; - -// Compute a partitioning of the vertices of the graph using the -// canonical views clustering algorithm. -// -// In the following we will use the terms vertices and views -// interchangably. Given a weighted Graph G(V,E), the canonical views -// of G are the the set of vertices that best "summarize" the content -// of the graph. If w_ij i s the weight connecting the vertex i to -// vertex j, and C is the set of canonical views. Then the objective -// of the canonical views algorithm is -// -// E[C] = sum_[i in V] max_[j in C] w_ij -// - size_penalty_weight * |C| -// - similarity_penalty_weight * sum_[i in C, j in C, j > i] w_ij -// -// alpha is the size penalty that penalizes large number of canonical -// views. -// -// beta is the similarity penalty that penalizes canonical views that -// are too similar to other canonical views. -// -// Thus the canonical views algorithm tries to find a canonical view -// for each vertex in the graph which best explains it, while trying -// to minimize the number of canonical views and the overlap between -// them. -// -// We further augment the above objective function by allowing for per -// vertex weights, higher weights indicating a higher preference for -// being chosen as a canonical view. Thus if w_i is the vertex weight -// for vertex i, the objective function is then -// -// E[C] = sum_[i in V] max_[j in C] w_ij -// - size_penalty_weight * |C| -// - similarity_penalty_weight * sum_[i in C, j in C, j > i] w_ij -// + view_score_weight * sum_[i in C] w_i -// -// centers will contain the vertices that are the identified -// as the canonical views/cluster centers, and membership is a map -// from vertices to cluster_ids. The i^th cluster center corresponds -// to the i^th cluster. -// -// It is possible depending on the configuration of the clustering -// algorithm that some of the vertices may not be assigned to any -// cluster. In this case they are assigned to a cluster with id = -1; -void ComputeCanonicalViewsClustering( - const CanonicalViewsClusteringOptions& options, - const WeightedGraph<int>& graph, - vector<int>* centers, - HashMap<int, int>* membership); - -struct CanonicalViewsClusteringOptions { - CanonicalViewsClusteringOptions() - : min_views(3), - size_penalty_weight(5.75), - similarity_penalty_weight(100.0), - view_score_weight(0.0) { - } - // The minimum number of canonical views to compute. - int min_views; - - // Penalty weight for the number of canonical views. A higher - // number will result in fewer canonical views. - double size_penalty_weight; - - // Penalty weight for the diversity (orthogonality) of the - // canonical views. A higher number will encourage less similar - // canonical views. - double similarity_penalty_weight; - - // Weight for per-view scores. Lower weight places less - // confidence in the view scores. - double view_score_weight; -}; - -} // namespace internal -} // namespace ceres - -#endif // CERES_NO_SUITESPARSE -#endif // CERES_INTERNAL_CANONICAL_VIEWS_CLUSTERING_H_ |