HUMAN DETECTION APPARATUS AND METHOD
First Claim
1. A human detection apparatus comprising:
- an image preprocessing unit for modeling a background image from an input image;
a moving object area setting unit for setting a moving object area in which motion is present by obtaining a difference between the input image and the background image;
a human region detection unit for extracting gradient-based feature vectors for a whole body and an upper body from the moving object area, and detecting a human region in which a person is present by using the gradient-based feature vectors for the whole body and the upper body as input of a neural network classifier; and
a decision unit for deciding whether an object in the detected human region is a person or a non-person.
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Abstract
Disclosed herein is an apparatus and method for detecting a person from an input video image with high reliability by using gradient-based feature vectors and a neural network. The human detection apparatus includes an image preprocessing unit for modeling a background image from an input image. A moving object area setting unit sets a moving object area in which motion is present by obtaining a difference between the input image and the background image. A human region detection unit extracts gradient-based feature vectors for a whole body and an upper body from the moving object area, and detects a human region in which a person is present by using the gradient-based feature vectors for the whole body and the upper body as input of a neural network classifier. A decision unit decides whether an object in the detected human region is a person or a non-person.
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Citations
13 Claims
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1. A human detection apparatus comprising:
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an image preprocessing unit for modeling a background image from an input image; a moving object area setting unit for setting a moving object area in which motion is present by obtaining a difference between the input image and the background image; a human region detection unit for extracting gradient-based feature vectors for a whole body and an upper body from the moving object area, and detecting a human region in which a person is present by using the gradient-based feature vectors for the whole body and the upper body as input of a neural network classifier; and a decision unit for deciding whether an object in the detected human region is a person or a non-person. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A human detection method comprising:
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modeling, by an image preprocessing unit, a background image from an input image; setting, by a moving object area setting unit, a moving object area in which motion is present by obtaining a difference between the input image and the background image; extracting, by a human region detection unit, gradient-based feature vectors for a whole body and an upper body from the moving object area; detecting, by the human region detection unit, a human region in which a person is present by using the gradient-based feature vectors for the whole body and the upper body as input of a neural network classifier; and deciding, by a decision unit, whether an object in the detected human region is a person or a non-person. - View Dependent Claims (11, 12, 13)
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Specification