Part based model and spatial-temporal reasoning to recognize hydraulic excavators in construction images and videos

被引：113

作者：

Azar, Ehsan Rezazadeh ^{[1
]}

McCabe, Brenda ^{[1
]}

机构：

[1] Univ Toronto, Dept Civil Engn, Toronto, ON M5S 1A4, Canada

来源：

AUTOMATION IN CONSTRUCTION | 2012年 / 24卷

关键词：

Computer vision; Object recognition; Earthmoving equipment; Automated data collection; Digital images; Spatial-temporal reasoning;

D O I：

10.1016/j.autcon.2012.03.003

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Detection of earthmoving equipment in construction images and videos can increase the automation level of many construction management tasks such as productivity measurement, locating of machines, work-zone safety, and semantic image and video indexing. Some of the earthmoving plants, such as hydraulic excavator, have articulated shapes making them a difficult target for even state of the art object recognition algorithms. The goal of this paper is to develop a model for non-rigid equipment detection and pose estimation in construction images and videos. In this paper, we describe an object recognition system based on mixture of appearances of deformable body parts of the hydraulic excavator and compare its results with general Histogram of Oriented Gradient detectors in both images and videos. Then a spatial-temporal reasoning model is presented which uses time and space constraints of the excavators' moving patterns to improve the detection results in videos. (C) 2012 Elsevier B.V. All rights reserved.

引用

页码：194 / 202

页数：9

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