JP5500559B2 - 物体検出装置 - Google Patents
物体検出装置 Download PDFInfo
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- JP5500559B2 JP5500559B2 JP2011518466A JP2011518466A JP5500559B2 JP 5500559 B2 JP5500559 B2 JP 5500559B2 JP 2011518466 A JP2011518466 A JP 2011518466A JP 2011518466 A JP2011518466 A JP 2011518466A JP 5500559 B2 JP5500559 B2 JP 5500559B2
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/4802—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
- G01S17/894—3D imaging with simultaneous measurement of time-of-flight at a 2D array of receiver pixels, e.g. time-of-flight cameras or flash lidar
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/50—Extraction of image or video features by performing operations within image blocks; by using histograms, e.g. histogram of oriented gradients [HoG]; by summing image-intensity values; Projection analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/60—Type of objects
- G06V20/64—Three-dimensional objects
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/103—Static body considered as a whole, e.g. static pedestrian or occupant recognition
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20021—Dividing image into blocks, subimages or windows
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- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Multimedia (AREA)
- Radar, Positioning & Navigation (AREA)
- Computer Networks & Wireless Communication (AREA)
- Remote Sensing (AREA)
- Electromagnetism (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Human Computer Interaction (AREA)
- Image Analysis (AREA)
- Measurement Of Optical Distance (AREA)
- Optical Radar Systems And Details Thereof (AREA)
- Length Measuring Devices By Optical Means (AREA)
Description
of Flight)カメラを用いている。本実施形態では、距離画像取得部10を3次元座標が固定された固定式カメラとして構成している。
識別部23の学習には、学習用サンプル(学習用距離画像)が用いられる。学習用サンプルは、検出対象画像(人の画像)であるポジティブクラスと非検出対象画像(人以外の画像)のネガティブクラスからなる。ポジティブクラスは、検出対象である確信度が高い正事例であり、ネガティブクラスは、検出対象である確信度が低い負事例である。リアル・アダブーストでは、ポジティブクラスの特徴量とネガティブクラスの特徴量の各次元の確率密度から分離度を求め、ポジティブクラスとネガティブクラスを最も分離できる特徴量を弱識別器として選択する。このとき分離度を評価値とするため、実数による識別結果の出力が可能である。
以上、本発明の実施形態について説明したが、本発明はこれに限定されるものではなく、各請求項に記載した範囲を逸脱しない限り、各請求項の記載文言に限定されず、当業者がそれらから容易に置き換えられる範囲にも及び、かつ、当業者が通常有する知識に基づく改良を適宜付加することができる。
Claims (4)
- 被写体までの距離を表す距離情報を取得し、前記距離情報を各画素の情報とする距離画像を取得する距離画像取得手段と、
前記距離画像中の所定領域に含まれる前記画素の距離情報を所定距離毎に分類して、距離ヒストグラムを作成する距離ヒストグラム作成手段と、
前記距離画像中の位置が異なる2つの前記所定領域の前記距離ヒストグラムの類似度を特徴量として算出する特徴量算出手段と、
確信度の高い学習用距離画像を正事例とし、確信度の低い学習用距離画像を負事例として、それらを識別するのに適した識別器を構築するとともに、前記識別器を用いて前記特徴量に基づいて前記距離画像から検出対象である物体を検出する識別手段とを備えることを特徴とする物体検出装置。 - 前記識別手段は、
前記所定領域に含まれる前記画素の距離情報が所定の閾値より近い距離を示すものである場合に、当該画素をオクルージョンと判定するオクルージョン判定手段と、
前記所定領域中における前記オクルージョンと判定された前記画素の割合であるオクルージョン率を算出するオクルージョン率算出手段と、
前記オクルージョン率を用いて前記識別器を構築する識別器構築手段とを備えることを特徴とする請求項1に記載の物体検出装置。 - 前記距離画像生成手段は、3次元空間における位置が固定されており、前記距離画像を含んだ全体距離画像を取得し、3次元空間でラスタスキャンを行うことで、前記全体距離画像から前記物体に対応した前記距離画像を取得することを特徴とする請求項1または2に記載に物体検出装置。
- 前記識別手段は、TOFカメラであることを特徴とする請求項1ないし3のいずれか1つに記載の物体検出装置。
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JP2011518466A JP5500559B2 (ja) | 2009-06-03 | 2010-06-02 | 物体検出装置 |
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JP2009133698 | 2009-06-03 | ||
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PCT/JP2010/059326 WO2010140613A1 (ja) | 2009-06-03 | 2010-06-02 | 物体検出装置 |
JP2011518466A JP5500559B2 (ja) | 2009-06-03 | 2010-06-02 | 物体検出装置 |
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JPWO2010140613A1 JPWO2010140613A1 (ja) | 2012-11-22 |
JP5500559B2 true JP5500559B2 (ja) | 2014-05-21 |
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JP (1) | JP5500559B2 (ja) |
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Cited By (1)
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JPWO2010140613A1 (ja) | 2012-11-22 |
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US8611604B2 (en) | 2013-12-17 |
US20120076361A1 (en) | 2012-03-29 |
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