Object Recognition Based on Representative Score Features

Anu Singha, M. Bhowmik
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引用次数: 3

Abstract

In this paper, we present an approach towards object detection and recognition from various environmental conditions such as foggy morning, dust scenarios, and night vision. The goal of the approach is to develop a holistic feature extraction method over object image patch. To categorize objects, the experimental evaluation has prepared through four classifiers. Investigational results with our own collected video sequences are reported to demonstrate the accuracy of the proposed approach.
基于代表性分数特征的目标识别
在本文中,我们提出了一种不同环境条件下的目标检测和识别方法,如多雾的早晨,灰尘场景和夜视。该方法的目标是开发一种基于目标图像补丁的整体特征提取方法。为了对对象进行分类,通过四个分类器准备了实验评价。研究结果与我们自己收集的视频序列报告,以证明所提出的方法的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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