-
- Yu Jaehoon
- Graduate School of Information Science and Technology, Osaka University
-
- Miyamoto Ryusuke
- Graduate School of Information Science and Technology, Osaka University
-
- Onoye Takao
- Graduate School of Information Science and Technology, Osaka University
Bibliographic Information
- Other Title
-
- CoHOG 特徴を用いた歩行者検出の確率的サンプリングに基づく高速化
- COHOG トクチョウ オ モチイタ ホコウシャ ケンシュツ ノ カクリツテキ サンプリング ニ モトズク コウソクカ
Search this article
Abstract
Pedestrian detection required for numerous practical applications is one of the most challenging problems. Recently, accurate schemes for pedestrian detection have been proposed and achieved acceptable detection accuracy for several practical applications. However, the increase of computational complexity becomes a significant problem, because most recent schemes adopt sophisticated feature descriptors and advanced machine learning algorithms. To solve this problem, computational complexity reduction schemes and parallel implementations using hardware and multi-core processors are proposed, but the processing speed still remains insufficient for real-time computation. Considering this background, we propose an acceleration scheme that can be combined with existing schemes, and show experimental results using CoHOG-based pedestrian detection. In the proposed scheme, the number of sampling is reduced by efficient sampling based on the probability distribution computed from the results of sliding window detection at reference images. Experimental results using INRIA data set show that the proposed scheme can compute about 2.5 times as fast as the original implementation without any degradation of detecting accuracy where false positive per image (FPPI) is adopted as a measure.
Journal
-
- The Journal of the Institute of Image Electronics Engineers of Japan
-
The Journal of the Institute of Image Electronics Engineers of Japan 42 (1), 30-40, 2013
The Institute of Image Electronics Engineers of Japan
- Tweet
Details 詳細情報について
-
- CRID
- 1390001204611500032
-
- NII Article ID
- 130004870601
-
- NII Book ID
- AA12563298
-
- ISSN
- 2186716X
- 13480316
- 02859831
-
- NDL BIB ID
- 024281537
-
- Text Lang
- ja
-
- Data Source
-
- JaLC
- NDL
- CiNii Articles
- KAKEN
-
- Abstract License Flag
- Disallowed