Mercurial > hg > camir-aes2014

annotate core/magnatagatune/ClipSimGraph.m @ 0:e9a9cd732c1e tip

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
first hg version after svn
author wolffd
date Tue, 10 Feb 2015 15:05:51 +0000
parents
children
rev   line source
wolffd@0 1 % ---
wolffd@0 2 % class ClipSimGraph
wolffd@0 3 % Directed graph representing comparative clip similarities.
wolffd@0 4 %
wolffd@0 5 % each node represents a pair of clips,
wolffd@0 6 % an edge (a,b) -> (a,c) is present if there is at least one
wolffd@0 7 % users judging clip a more similar to clip b than to clip c
wolffd@0 8 %
wolffd@0 9 % The Edges thus represent the (are nearer to each othen than)
wolffd@0 10 % expression
wolffd@0 11 % ---
wolffd@0 12
wolffd@0 13 classdef ClipSimGraph < ClipPairGraph
wolffd@0 14
wolffd@0 15 % ---
wolffd@0 16 % the methods
wolffd@0 17 % ---
wolffd@0 18 methods
wolffd@0 19
wolffd@0 20
wolffd@0 21 % constructor of the graph
wolffd@0 22 function G = ClipSimGraph(comparison, comparison_ids)
wolffd@0 23
wolffd@0 24 % ---
wolffd@0 25 % handle manual input
wolffd@0 26 % ---
wolffd@0 27
wolffd@0 28 if nargin == 1
wolffd@0 29 % ---
wolffd@0 30 % this uses an imput grpaph
wolffd@0 31 % to create a new MD graph
wolffd@0 32 % ---
wolffd@0 33
wolffd@0 34 G = ClipSimGraph();
wolffd@0 35
wolffd@0 36 % ---
wolffd@0 37 % Add the input graph to the empty one
wolffd@0 38 % ---
wolffd@0 39 G.add_graph(comparison);
wolffd@0 40
wolffd@0 41 % ---
wolffd@0 42 % TODO: Copy Clip Pair Information if neccessary
wolffd@0 43 % this is by now a handle copy
wolffd@0 44 % ---
wolffd@0 45 clas = cat(1, class(comparison), superclasses(comparison));
wolffd@0 46 if strcellfind(clas, 'ClipPairGraph')
wolffd@0 47
wolffd@0 48 G.vid_map = comparison.vid_map;
wolffd@0 49 end
wolffd@0 50
wolffd@0 51 elseif nargin == 2
wolffd@0 52
wolffd@0 53 % ---
wolffd@0 54 % handle automatic or manual input
wolffd@0 55 % ---
wolffd@0 56 for i = 1:size(comparison,1)
wolffd@0 57
wolffd@0 58 % get clips and votes
wolffd@0 59 clips = comparison_ids(comparison(i,1:3));
wolffd@0 60 votes = comparison(i,4:6);
wolffd@0 61
wolffd@0 62 % for each triplet position create an edge reflecting the
wolffd@0 63 % absolute and relative voting for this position
wolffd@0 64
wolffd@0 65 % ---
wolffd@0 66 % NOTE: we index 0 - 2 to ease the mod
wolffd@0 67 % calculaton for the remaining indices
wolffd@0 68 % ---
wolffd@0 69 for v = 0:2
wolffd@0 70
wolffd@0 71 % ---
wolffd@0 72 % has at least one user voted this clip out?
wolffd@0 73 % If so, treat it as an outlier and determine score
wolffd@0 74 % ---
wolffd@0 75 if votes(v+1) > 0
wolffd@0 76
wolffd@0 77 a = mod(v+1, 3)+1;
wolffd@0 78 b = mod(v+2, 3)+1;
wolffd@0 79 c = v+1;
wolffd@0 80
wolffd@0 81 % ---
wolffd@0 82 % TODO: how to determine the weight?
wolffd@0 83 % There are two options: relative in the triple
wolffd@0 84 % and counting absolute hits.
wolffd@0 85 % first we go for the relative ones.
wolffd@0 86 % The other is implemented in ClipSimGraphMulti
wolffd@0 87 % ---
wolffd@0 88
wolffd@0 89 % ---
wolffd@0 90 % add an edge saying sim(a,b) > sim(a,c)
wolffd@0 91 % ---
wolffd@0 92 G.add_edge(clips(a), clips(b), clips(c), votes(c) / (sum(votes)));
wolffd@0 93
wolffd@0 94 % ---
wolffd@0 95 % every outlier vote results in two
wolffd@0 96 % dissimilarity equations
wolffd@0 97 % ---
wolffd@0 98
wolffd@0 99 % edge 2
wolffd@0 100 G.add_edge(clips(b), clips(a), clips(c), votes(c) / (sum(votes)));
wolffd@0 101
wolffd@0 102 end
wolffd@0 103
wolffd@0 104 end
wolffd@0 105 end
wolffd@0 106 end
wolffd@0 107
wolffd@0 108 end
wolffd@0 109
wolffd@0 110 % end constructor function
wolffd@0 111
wolffd@0 112
wolffd@0 113 function [weights, a, b, c] = similarities(G)
wolffd@0 114 % ---
wolffd@0 115 % returns the weights of edges meaning sim(a,b) > sim(a,c)
wolffd@0 116 % ---
wolffd@0 117 % get edge weights
wolffd@0 118 [weights, a, b, c] = edges(G);
wolffd@0 119 end
wolffd@0 120
wolffd@0 121 % ---
wolffd@0 122 % add an edge saying sim(a,b) > sim(a,c)
wolffd@0 123 % ---
wolffd@0 124 % function add_edge(G, a, b, c, weight)
wolffd@0 125
wolffd@0 126 function remove_edge(G, a, b, c)
wolffd@0 127
wolffd@0 128 if nargin == 4
wolffd@0 129 V1 = add_node(G, a, b);
wolffd@0 130 V2 = add_node(G, a, c);
wolffd@0 131
wolffd@0 132 elseif nargin == 3
wolffd@0 133 V1 = a;
wolffd@0 134 V2 = b;
wolffd@0 135 end
wolffd@0 136
wolffd@0 137 % ---
wolffd@0 138 % call superclass
wolffd@0 139 % ---
wolffd@0 140 remove_edge@DiGraph(G, V1, V2);
wolffd@0 141 end
wolffd@0 142
wolffd@0 143 function set_edge(G, a, b, c, weight)
wolffd@0 144 if nargin == 5
wolffd@0 145 V1 = add_node(G, a, b);
wolffd@0 146 V2 = add_node(G, a, c);
wolffd@0 147
wolffd@0 148 elseif nargin == 4
wolffd@0 149 V1 = a;
wolffd@0 150 V2 = b;
wolffd@0 151 weight = c;
wolffd@0 152 end
wolffd@0 153
wolffd@0 154 % ---
wolffd@0 155 % call superclass
wolffd@0 156 % ---
wolffd@0 157 set_edge@DiGraph(G, V1, V2, weight);
wolffd@0 158 end
wolffd@0 159
wolffd@0 160 % ---
wolffd@0 161 % simple mix of two sets of info about the same
wolffd@0 162 % nodes: mean.
wolffd@0 163 % NOTE: if there's more than two infos, the earlier
wolffd@0 164 % information will loose influence
wolffd@0 165 % ---
wolffd@0 166 function join_edge(G, a, b, c, weight)
wolffd@0 167
wolffd@0 168 if nargin == 5
wolffd@0 169 V1 = G.node(a, b);
wolffd@0 170 V2 = G.node(a, c);
wolffd@0 171 elseif nargin == 4
wolffd@0 172 V1 = a;
wolffd@0 173 V2 = b;
wolffd@0 174 weight = c;
wolffd@0 175 end
wolffd@0 176
wolffd@0 177 if G.edge(V1, V2) ~= 0
wolffd@0 178
wolffd@0 179 % set Edge to weight
wolffd@0 180 G.E(V1, V2) = (G.E(V1, V2) + weight) /2;
wolffd@0 181
wolffd@0 182 cprint(4, 'edge weight %d %d %d updated \n',a ,b , c) ;
wolffd@0 183 else
wolffd@0 184
wolffd@0 185 error 'nodes not found';
wolffd@0 186 end
wolffd@0 187 end
wolffd@0 188 end
wolffd@0 189 end
wolffd@0 190
wolffd@0 191