Apparatus and method for detecting object

Patent metadata

Field	Value
Publication number	US-2016358039-A1
Application number	US-201615164215-A
Country	US
Kind code	A1
Filing date	May 25, 2016
Priority date	Jun 2, 2015
Publication date	Dec 8, 2016
Grant date	—

Abstract

An apparatus for object detection according to an example includes a level image generating unit configured to generate a plurality of level images with reference to a target image; a feature vector extracting unit configured to extract a feature vector from each level image; a codeword generating unit configured to generate a codeword by clustering the feature vector for each level image; a histogram generating unit configured to generate a histogram corresponding to the codeword; and a classifier configured to generate object recognition information of the target image based on the histogram.

First claim

What is claimed is:

1 . An apparatus for object detection comprising:
a level image generating unit configured to generate a plurality of level images with reference to a target image; a feature vector extracting unit configured to extract a feature vector from each level image; a codeword generating unit configured to generate a codeword by clustering the feature vector for each level image; a histogram generating unit configured to generate a histogram corresponding to the codeword; and a classifier configured to generate object recognition information of the target image based on the histogram.

2 . The apparatus of claim 1 , wherein the histogram generating unit generates a hierarchical histogram by combining histograms corresponding to the codewords for the level images, and the classifier generates object recognition information of the target image based on the hierarchical histogram.

3 . The apparatus of claim 1 , wherein when patches with a predetermined size is listed on the level image, the feature vector extracting unit extracts a feature vector of a pixel in each patch.

4 . The apparatus of claim 3 , wherein the feature vector extracting unit divides the patch into predetermined-sized sub-patches and extracts a uniform local binary pattern feature vector for each sub-patch.

5 . The apparatus of claim 1 , wherein the codeword generating unit clusters the feature vector using a K-means clustering method to classify into one or more clusters, and generate a codeword for each cluster.

6 . The apparatus of claim 1 , wherein the level image generating unit generates a plurality of level images with reference to a training image, and the classifier performs training based on the hierarchical histogram corresponding to the training image.

7 . The apparatus of claim 1 , wherein the classifier is a support vector machine.

8 . A method for object detection in which an apparatus for object detection recognizes objects of an image, the method comprising:
generating a plurality of level images with reference to a target image; extracting a feature vector from each level image; generating a codeword by clustering the feature vector for each level image; generating a histogram corresponding to the codeword; and generating object recognition information of the target image based on the histogram using a classifier.

9 . The method of claim 8 , wherein the generating a histogram corresponding to the codeword comprises generating a hierarchical histogram by combining histograms corresponding to the codewords for the level images, and
the generating object recognition information of the target image based on the histogram using a classifier comprises generating object recognition information of the target image based on the hierarchical histogram.

10 . The method of claim 8 , wherein the extracting a feature vector from each level image comprises, when patches with a predetermined size are listed on the level image, extracting a feature vector of a pixel in each patch.

11 . The method of claim 10 , wherein the extracting a feature vector from each level image comprises dividing the patch into predetermined-sized sub-patches and extracting a uniform local binary pattern feature vector for each sub-patch.

12 . The method of claim 8 , wherein the generating a codeword by clustering the feature vector for each level image comprises clustering the feature vector using a K-means clustering method to classify into one or more clusters, and generating a codeword for each cluster.

13 . The method of claim 8 , further comprising:
generating a plurality of level images with reference to a training image; and performing training based on the hierarchical histogram corresponding to the training image.

14 . The method of claim 8 , wherein the classifier is a support vector machine.

Assignees

• Electronics & Telecommunications Res Inst

Inventors

• Ko Jong-Gook
• Park Kyoung
• Park Jong-Youl
• HWANG Joong-Won

Classifications

• G06V10/809

  of classification results, e.g. where the classifiers operate on the same input data · CPC title

• G06F18/254

  of classification results, e.g. of results related to same input data · CPC title

• G06V10/507 Primary

  Summing image-intensity values; Histogram projection analysis · CPC title

• G06K9/6212 Primary

  Physics · mapped topic

• G06K9/481

  Physics · mapped topic