Performance Analysis of the SIFT Operator for Automatic Feature Extraction and Matching in Photogrammetric Applications

نویسندگان

  • Andrea Lingua
  • Davide Marenchino
  • Francesco Nex
چکیده

In the photogrammetry field, interest in region detectors, which are widely used in Computer Vision, is quickly increasing due to the availability of new techniques. Images acquired by Mobile Mapping Technology, Oblique Photogrammetric Cameras or Unmanned Aerial Vehicles do not observe normal acquisition conditions. Feature extraction and matching techniques, which are traditionally used in photogrammetry, are usually inefficient for these applications as they are unable to provide reliable results under extreme geometrical conditions (convergent taking geometry, strong affine transformations, etc.) and for bad-textured images. A performance analysis of the SIFT technique in aerial and close-range photogrammetric applications is presented in this paper. The goal is to establish the suitability of the SIFT technique for automatic tie point extraction and approximate DSM (Digital Surface Model) generation. First, the performances of the SIFT operator have been compared with those provided by feature extraction and matching techniques used in photogrammetry. All these techniques have been implemented by the authors and validated on aerial and terrestrial images. Moreover, an auto-adaptive version of the SIFT operator has been developed, in order to improve the performances of the SIFT detector in relation to the texture of the images. The Auto-Adaptive SIFT operator (A(2) SIFT) has been validated on several aerial images, with particular attention to large scale aerial images acquired using mini-UAV systems.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Sub-Harris Operator Coupled with SIFT for Fast Images Matching in Low-altitude Photogrammetry

Fast and robust images matching are of vital importance in low-altitude photogrammetric process. Among the most popular features of images matching are currently SIFT and Harris etc. For time-critical applications such as disaster monitoring, the SIFT features extraction are too slow, and the location accuracy of SIFT and Harris is insufficient in photogrammetric process. In this paper, we pres...

متن کامل

Low-cost Uav for the Environmental Emergency Management. Photogrammetric Procedures for Rapid Mapping Activities

The main research topic of this PhD thesis is the analysis and the development of photogrammetric procedures for the processing of digital images acquired by an Unmanned Aerial Vehicle (UAV). The mini-UAV “Pelican” is a low-cost aerial platform capable of autonomous flight and equipped with a photogrammetric payload for rapid mapping purposes. It has been developed by ITHACA (Information Techno...

متن کامل

Performance Evaluation of Local Detectors in the Presence of Noise for Multi-Sensor Remote Sensing Image Matching

Automatic, efficient, accurate, and stable image matching is one of the most critical issues in remote sensing, photogrammetry, and machine vision. In recent decades, various algorithms have been proposed based on the feature-based framework, which concentrates on detecting and describing local features. Understanding the characteristics of different matching algorithms in various applications ...

متن کامل

Automatic Face Recognition via Local Directional Patterns

Automatic facial recognition has many potential applications in different areas of humancomputer interaction. However, they are not yet fully realized due to the lack of an effectivefacial feature descriptor. In this paper, we present a new appearance based feature descriptor,the local directional pattern (LDP), to represent facial geometry and analyze its performance inrecognition. An LDP feat...

متن کامل

Adaptive Principle Component Analysis to Improve Scale Invariant Feature Transform Matching for Face Recognition Applications

Image matching using feature extraction is an important issue in computer vision tasks. The main drawback of matching process is the bottleneck problem that rapidly appeared when the number of features increased. This paper produced an adaptive approach to improve Scale Invariant Feature Transform (SIFT) matching. The main idea is to increase the number of SIFT points by using Adaptive PCA in w...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره 9  شماره 

صفحات  -

تاریخ انتشار 2009