JOURNAL ARTICLE

A Fast Object Detection Method With Rotation Invariant Features

Zilong HeYuesheng Zhu

Year: 2011 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

Based on the combined shape feature and texture feature, a fast object detection method with rotation invariant features is proposed in this paper. A quick template matching scheme based online learning designed for online applications is also introduced in this paper. The experimental results have shown that the proposed approach has the features of lower computation complexity and higher detection rate, while keeping almost the same performance compared to the HOG-based method, and can be more suitable for run time applications.

Keywords:
Artificial intelligence Computer vision Invariant (physics) Rotation (mathematics) Computer science Pattern recognition (psychology) Mathematics

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Topics

Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering
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