JP2010520542A - 分類器チェーンを用いた照明検出 - Google Patents
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Abstract
【選択図】図9A
Description
ビオラ-ジョーンズ(Viola-Jones)は、一連の連続する特徴検出器からなる分類器チェーン(classifier chain)を提案する。分類器チェーンは、顔を表さない画像パターンを拒絶し、顔を表す画像パターンを許諾する。
図1は、特定の実施形態による、顔検出及び顔追跡システムのサブシステムを説明する。実線は画像データの流れを示し、破線はモジュールからの情報出力(例えば検出された顔の位置)又は制御入力を示す。本実施例において、画像処理装置としては、デジタルスチルカメラ(DSC)、ビデオカメラ、画像取得メカニズムを備える携帯電話、又は内蔵若しくは外付けカメラを備えるノートパソコンなどがある。
例えば、図4で説明される画像解析モジュール1156は、画像1170−1…1180−2のセットを循環し、顔領域及び関連した周辺領域を決定、抽出、正規化、及び解析し、複数の顔と非顔の分類器に対して特徴ベクトルを決定する。次にモジュールは、この抽出された情報を画像データセット履歴に記録する。このモジュールの構成要素は、実施形態の訓練モード及び並び替え/検索モードの両方に同様に用いられる。モジュールは、上位レベルのワークフローから呼び出され、その通常モードの使用において、画像のセットを移し、図7において説明されるように、解析される[2202]。モジュールは、次の画像をロード/取得し[2202]、画像[2204]において任意の顔領域を検出する。顔領域が検出できなかった場合には、その画像に対する画像データ履歴におけるフラグは、顔領域が検出されなかったことを示すために更新される。現在の画像が、解析されている画像のセットの最終画像である場合には[2208]、画像副標本化[2232]、顔と周辺領域の抽出[2206]、及び領域正規化[2207]がされ次第、次の画像がロードされる/取得される[2204]。これが最終画像であった場合には、モジュールは、呼び出し側モジュールを終了する。少なくとも一の顔領域が検出される場合には、次にモジュールは各検出された顔領域、可能な場合にはいずれかの関連する周辺領域、を抽出及び正規化する。
図5及び図6Aから6Fで説明される、画像の並び替え/検索処理又はモジュールに関するワークフローは、最終処理ステップ[1140]として、画像選択又は取得処理から開始される(米国特許出願公開第2006/0140455号明細書参照)。画像の並び替え/検索モジュールが起動される場合には[1140]、同様に少なくとも2つの入力パラメーラが備わっており、(i)検索/並び替え/分類の基準の決定に用いられる画像、及び(ii)検索が実行される画像集のデータセット、へのアクセスを提供すると憶測する。データ履歴が利用不可能と決定され、画像における人物及び検索基準を選択する[1308]検索画像に対していまだに決定されていない場合[1306]には、このデータ履歴を生成するために、主画像解析モジュールは次にそれに適用される[1200]。画像は次に、検索に用いられる顔領域及び/又は検索に用いられる分類器の特定の選択をするために、オプションを提供される場合があるユーザに対して表示される[1308]。或いは、検索基準は、あらかじめ定められる場合や、別に構成ファイル及びステップを介して自動化される場合があり、従って自動である場合がある[1308]。ユーザインターフェイスの態様は、米国特許出願公開第2006/0140455号明細書により詳細に記載される。
(統計的正規化方法)
好ましくは、複数の分類器を正規化及び組み合わせるために技術が用いられ、最終類似ランキングに達する。処理は、複数の分類器のセットC1、C2、・・・、Cnに影響を及ぼす場合があり、選択された参照領域からの現在の分類器に関連する全てのパターンについての距離の分布の統計的決定(実施例において、顔又は周辺領域)に基づく場合がある。大部分の分類器に関して、この統計的解析は一般的に、平均値Mcn及び分散Vcnとともに正規分布を生じる。
画像装置は、演算能力、メモリ、及び非揮発性記録装置を増加し続けるから、カメラ内画像の並び替えサブシステムとして多くの利点が提供されることは、デジタルカメラの設計に関する当業者に明らかである。模範的な実施形態は、図7に説明される。
分岐した分類器チェーンは、顔の同時分類及び不均一(又は均一)な照明の同時分類に用いられる場合がある。特定の実施形態において、分類器チェーンは、初期の特徴検出器のセットが、非顔として画像内の被写体の大部分を拒絶した後に、例えば、3、4、5、6、7、8、又は9などの特徴検出器のセットを適用するように構成される。特徴検出器は、上側、下側、及び左側若しくは右側の照明(顔が左右対称であるから);上側、下側、左側若しくは右側、及び均一の照明;上側、下側、左側、右側、及び均一の照明;上側、左側、右側、下側、右下側、左下側、右上側、及び左上側の照明;上側、左側、右側、下側、右上側、左上側、右下側、左下側、及び均一の照明;又は、上側、下側、右側若しくは左側若しくはその両方、右上側若しくは左上側若しくはその両方、右下側若しくは左下側若しくはその両方、及び均一の照明、から照らされる顔を許諾するために、調整される場合がある。他の組み合わせは可能であり、例えば、画像内又は特定の照明である画像のサブウィンドウ内に顔が存在するかの決定を提供する一の分類器の適用後に、一部が除外される場合がある。分類器分岐の内の一つが顔を許諾する場合には、顔及び顔の照明が検出されたと言える。この検出は、非顔よりも顔により注目して画像の処理に用いることができ、及び/又は不均一な照明状態の修正に用いることができ、顔認識結果を改善する。
Chain1 = cls11 + cls12 + ・・・ + cls1M
・・・
ChainN = clsN1 + clsN2 + ・・・ + clsNM
Partial1 = cls11 + cls12 + ・・・ + cls1P
・・・
PartialN = clsN1 + clsN2 + ・・・ + clsNP, with P < M
ChainMax = PartialMax + clsMax(P+1) + clsMax(P+2) + ・・・ + clsMaxM
と継続して実行する。
Partial1 ---
... \
PartialMax --- (choose Max) -> continue with the rest of Max
... /
PartialN ---
である。
Claims (18)
- (a)不均一に照らされるであろう顔に相当するデータを含むデジタル画像を取得し、
(b)前記顔データに一以上の不均一な照明分類器プログラムを適用し、
(c)前記デジタル画像内の前記顔に相当するとして前記顔データを特定し、
(d)前記一以上の不均一な照明分類器プログラムの前記適用結果として、前記顔に対する不均一な照明状態を決定し、
(e)前記決定に基づいて、前記顔の前記不均一な照明状態を修正し、より均一な照明を有するであろう修正された顔画像を生成し、並びに、
(f)前記修正された顔画像を電子的に記録し、送信し、顔認識プログラムを前記修正された顔画像に適用し、編集し、若しくは表示する、又はその組み合わせ、
を含む顔の照明正規化方法。 - 顔認識プログラムを前記修正された顔画像に適用することを含む、請求項1に記載の方法。
- 前記顔の前記検出及び前記顔の前記不均一な照明状態の前記決定は同時に実行される、請求項1に記載の方法。
- 特徴検出器プログラムのセットを適用し、非顔データが顔データとして特定されることを拒絶することを含む、請求項1に記載の方法。
- 正面の照明分類器プログラムを前記顔データに適用することを含む、請求項1に記載の方法。
- 前記分類器プログラムの1つによる前記顔データの許諾に基づいて照明状態を決定することを含む、請求項5に記載の方法。
- 前記デジタル画像は、前記顔を含む一連の複数の画像の1つであり、前記修正は、前記照明状態が決定される前記デジタル画像よりも、一連の異なる画像に適用される、請求項6に記載の方法。
- 前記不均一な照明分類器プログラムは、上側の照明分類器、下側の照明分類器、及び右側と左側の照明分類器の一方又は両方を含む、請求項1に記載の方法。
- 正面の照明分類器プログラムを前記顔データに適用することを含む、請求項8に記載の方法。
- 前記適用は、照明状態が適用されず、前記顔データが顔として拒絶されないと決定する後に、少なくとも2つのフル分類器のセットを適用することを含む、請求項1に記載の方法。
- (a)デジタル画像を取得し、
(b)前記画像からサブウィンドウを抽出し、
(c)顔領域の特徴に対して選択的に敏感であるように訓練された、2以上の短縮された顔検出分類器カスケードを適用し、
(d)前記適用に基づいて、特定の前記特徴の形式を備える顔が前記サブウィンドウ内にある確率を決定し、
(e)前記決定に基づいて、前記特徴の前記形式に対する感度のために訓練された、拡張された顔検出分類器カスケードを適用し、
(f)前記画像サブウィンドウ内に顔が存在するかの最終決定を提供し、並びに、
(g)前記画像からの一以上の更なるサブウィンドウ若しくは一以上の更なる特徴又はその両方に対して、ステップ(b)から(e)を一回以上繰り返す、
ことを含む顔検出方法。 - 前記特徴は、前記顔領域の指向性照明、前記顔領域の面内回転、前記顔領域の3次元の姿勢バリエーション、笑顔度、まばたき度、ウィンク度、開口度、顔のぶれ、眼の欠陥、顔の陰、顔のオクルージョン、顔の色、若しくは顔の形、又はその組み合わせを含む、請求項11に記載の方法。
- 前記特徴は指向性照明を含み、前記方法は一以上の不均一な照明分類器カスケードを適用することにより、不均一な照明状態を決定することを含む、請求項11に記載の方法。
- 正面の照明分類器カスケードを適用することを含む、請求項13に記載の方法。
- 前記分類器カスケードの1つによる許諾に基づいて、サブウィンドウ内の顔の照明状態を決定することを含む、請求項14に記載の方法。
- 前記デジタル画像は前記顔を含む一連の複数の画像の1つであり、前記方法は前記照明状態が決定される前記デジタル画像よりも、一連の異なる画像内の前記顔の不均一な照明状態を修正することを含む、請求項15に記載の方法。
- 前記不均一な照明分類器カスケードは、上側の照明分類器、下側の照明分類器、及び右側と左側の照明分類器の一方又は両方を含む、請求項13に記載の方法。
- 前の請求項のいずれか1項に記載の、顔照明正規化方法を実行するために、デジタル画像を取得するためのオプトエレクトロニクスシステムと、プロセッサをプログラミングするために記録されたプロセッサが読取可能なコードを有するデジタルメモリとを含むデジタル画像取得装置。
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Cited By (12)
Publication number | Priority date | Publication date | Assignee | Title |
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JP2011514563A (ja) * | 2007-09-26 | 2011-05-06 | テセラ テクノロジーズ アイルランド リミテッド | カメラプロセッサーにおける顔トラッキング |
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Also Published As
Publication number | Publication date |
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EP2137670A2 (en) | 2009-12-30 |
US20120207358A1 (en) | 2012-08-16 |
KR20090118095A (ko) | 2009-11-17 |
WO2008107112A2 (en) | 2008-09-12 |
EP2137670B1 (en) | 2013-12-11 |
US8503800B2 (en) | 2013-08-06 |
WO2008107112A3 (en) | 2009-01-08 |
KR101129405B1 (ko) | 2012-03-26 |
US20080219517A1 (en) | 2008-09-11 |
JP5174045B2 (ja) | 2013-04-03 |
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