CMRT09

Stilla, Uwe

Bibliographic data

Monograph

Persistent identifier:: 856955019

Author:: Stilla, Uwe

Title:: CMRT09

Sub title:: object extraction for 3D city models, road databases, and traffic monitoring ; concepts, algorithms and evaluation ; Paris, France, September 3 - 4, 2009 ; [joint conference of ISPRS working groups III/4 and III/5]

Scope:: X, 234 Seiten

Year of publication:: 2009

Place of publication:: Lemmer

Publisher of the original:: GITC

Identifier (digital):: 856955019

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: STUDY OF SIFT DESCRIPTORS FOR IMAGE MATCHING BASED LOCALIZATION IN URBAN STREET VIEW CONTEXT David Picard, Matthieu Cord and Eduardo Valle

Document type:: Monograph

Structure type:: Chapter

In: Stilla U, Rottensteiner F, Paparoditis N (Eds) CMRT09. IAPRS, Vol. XXXVIII, Part 3/W4 — Paris, France, 3-4 September, 2009 STUDY OF SIFT DESCRIPTORS FOR IMAGE MATCHING BASED LOCALIZATION IN URBAN STREET VIEW CONTEXT David Picard 1 , Matthieu Cord 1 and Eduardo Valle 2 1 LIP6 UPMC Paris 6 104 avenue du Président Kennedy 75016 Paris FRANCE {david.picard, matthieu.cord} @lip6.fr 2 ETIS, CNRS, ENSEA, Univ Cergy-Pontoise, F-95000 Cergy-Pontoise mail @eduardovalle.com KEY WORDS: Image, Databases, Matching, Retrieval, Urban, High resolution ABSTRACT In this paper we evaluate the quality of vote-based retrieval using SIFT descriptors in a database of street view photog raphy, a challeging context where the fraction of mismatched descriptors tends to be very high. This work is part of the iTowns project, for which high resolution street views of Paris have been taken. The goal is to retrieve the views of a urban scene given a query picture. We have carried out experiments for several techniques of image matching, including a post-processing step to check the geometric consistency of the results. We have shown that the efficiency of SIFT based matching depends largely on the image database content, and that the post-processing step is essential to the retrieval performances. 1 INTRODUCTION In this paper, we evaluate the effectiveness of a voting strat egy using SIFT descriptors for near-duplicate retrieval of urban scenes. We have observed that, compared to previ ously repported applications of SIFT (object recognition, stereoscopy, etc.) (Lowe, 2003) this context presents the challenge of a very high rate of descriptor mismatches, due to the complexity of both the scene and the transfor mations it might suffer. We have thus, evaluated how dif ferent strategies to filter out the false matches can improve the effectiveness of retrieval. This study is part of the iTowns project, which is about defining a new generation of multimedia web tools that mixes a broadband 3D geographic image-based browser with an image-based search engine 1 . Fig. 1 shows an ex ample of pictures taken for the project. The first goal of the new type of search engine, is to re trieve, in the high-resolution database, the scene correspond ing to a given query image. Let us imagine the following scenario: a user is looking for information about a restau rant in front of him (feedback from patrons, for instance). He takes a picture of the restaurant with his phone and send it to the iTowns web server. The image is matched on the database and the desired information is retrieved and sent back to the user. In order to accomplish this goal, there is basically three steps to perform : 1. Match the query image with the corresponding scene in the database. 2. Find information associated with the scene and re lated to the query. 1 See http://itowns.ign.fr 3. Retrieve only relevant information regarding the user interests. In this paper, we focus on the first part, and consider the use of state of the art techniques for near-duplicate image matching. Recently, techniques have been developed for the detection of copies where transformations between im ages are well known (rotation, scaling, global illumination change etc). Those techniques involve the extraction of points of interest in the images, then the matching of the points in the query with the points in the database, and the aggregation of the matches for images of the database us ing a voting strategy. We try to extend these techniques to the matching of images with less constrainted, and thus more realistic transformations (change of viewpoint, local illumination, etc). The paper is organized as follows: the next section intro duces keypoint-based image matching. We explain in sec tion 3 the strategy used to perform an efficient approximate k-NN search in the database in order to associate query points with points in the database. Then, we detail in sec tion 4 the geometrical consistency used to filter irrelevant matches. Experiments are done on two representative sub sets of the iTowns collection, and results are shows in sec tion 5, before we conclude. 2 KEYPOINTS BASED IMAGE MATCHING The essential elements of keypoint-based image matching appeared in (Schmid and Mohr, 1997): the use of points of interest, local descriptors computed around those points, a dissimilarity criterion based on a vote-counting algorithm, and a step of consistency checking on the matches before the final vote count and ranking of the results. We use the SIFT points of interest (Lowe, 2003) to describe the

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