/**
* コンストラクタです。
* ファイルイメージからデータセットを生成します。
* @param i_iset
* @param i_fset
* @param i_freak_fset
* @param i_freak_fset_page_id
*/
public NyARNftDataSet(NyARNftIsetFile i_iset, NyARNftFsetFile i_fset, NyARNftFreakFsetFile i_freak_fset, int i_freak_fset_page_id, double i_width_in_msec)
{
if (!Double.IsNaN(i_width_in_msec))
{
scaling(i_iset, i_fset, i_freak_fset, i_freak_fset_page_id, i_width_in_msec);
}
this.surface_dataset = new NyARSurfaceDataSet(i_iset, i_fset);
this.freak_fset = new KeyframeMap(i_freak_fset, i_freak_fset_page_id);
}
/**
* 現在の特徴点セットから、
* @param i_keymap
* @param i_result
* @return
*/
public bool kpmMatching(KeyframeMap i_keymap, NyARDoubleMatrix44 i_transmat)
{
FeaturePairStack result = new FeaturePairStack(kMaxNumFeatures);
if (!this.query(this.mQueryKeyframe, i_keymap, result))
{
return(false);
}
return(kpmUtilGetPose_binary(this._ref_cparam, result, i_transmat, this._result_param));
}
private bool query(FreakFeaturePointStack query_keyframe, KeyframeMap i_keymap, FeaturePairStack i_result)
{
// mMatchedInliers.clear();
HomographyMat H = this._H;
InverseHomographyMat hinv = this._hinv;
hinv = new InverseHomographyMat_O1();
int num_of_query_frame = query_keyframe.getLength();
//ワークエリアの設定
if (num_of_query_frame > this._tmp_pair_stack[0].getArraySize())
{
this._tmp_pair_stack[0] = new FeaturePairStack(num_of_query_frame + 10);
this._tmp_pair_stack[1] = new FeaturePairStack(num_of_query_frame + 10);
}
int tmp_ch = 0;
int last_inliers = 0;
foreach (KeyValuePair <int, Keyframe> i in i_keymap)
{
Keyframe second = i.Value;
FreakMatchPointSetStack ref_points = second.getFeaturePointSet();
//新しいワークエリアを作る。
FeaturePairStack match_result = this._tmp_pair_stack[tmp_ch];
//ワークエリア初期化
match_result.clear();
//特徴量同士のマッチング
if (this._matcher.match(query_keyframe, second, match_result) < this.mMinNumInliers)
{
continue;
}
// Vote for a transformation based on the correspondences
if (!this.mHoughSimilarityVoting.extractMatches(match_result, second.width(), second.height()))
{
continue;
}
// Estimate the transformation between the two images
if (!this.mRobustHomography.PreemptiveRobustHomography(H, match_result, second.width(), second.height()))
{
continue;
}
//ここでHInv計算
if (!hinv.inverse(H))
{
continue;
}
// Apply some heuristics to the homography
if (!hinv.checkHomographyHeuristics(second.width(), second.height()))
{
continue;
}
// Find the inliers
this._find_inliner.extructMatches(H, match_result);
if (match_result.getLength() < mMinNumInliers)
{
continue;
}
//
// Use the estimated homography to find more inliers
match_result.clear();
if (_matcher.match(query_keyframe, ref_points, hinv, 10, match_result) < mMinNumInliers)
{
continue;
}
//
// Vote for a similarity with new matches
if (!this.mHoughSimilarityVoting.extractMatches(match_result, second.width(), second.height()))
{
continue;
}
//
// Re-estimate the homography
if (!this.mRobustHomography.PreemptiveRobustHomography(H, match_result, second.width(), second.height()))
{
continue;
}
// Apply some heuristics to the homography
if (!hinv.inverse(H))
{
continue;
}
if (!hinv.checkHomographyHeuristics(second.width(), second.height()))
{
continue;
}
//
// Check if this is the best match based on number of inliers
this._find_inliner.extructMatches(H, match_result);
//ポイント数が最小値より大きい&&最高成績ならテンポラリチャンネルを差し替える。
if (match_result.getLength() >= mMinNumInliers && match_result.getLength() > last_inliers)
{
//出力チャンネルを切り替え
tmp_ch = (tmp_ch + 1) % 2;
last_inliers = match_result.getLength();
}
}
//出力は last_inlines>0の場合に[(tmp_ch+1)%2]にある。
if (last_inliers <= 0)
{
return(false);
}
{
FeaturePairStack match_result = this._tmp_pair_stack[(tmp_ch + 1) % 2];
FeaturePairStack.Item[] dest = match_result.getArray();
for (int i = 0; i < match_result.getLength(); i++)
{
FeaturePairStack.Item t = i_result.prePush();
if (t == null)
{
System.Console.WriteLine("Push overflow!");
break;
}
t.query = dest[i].query;
t.ref_ = dest[i].ref_;
}
}
return(true);
}
