MULTIVARIATE LOG-GAUSSIAN COX MODELS OF ELEMENTARY SHAPES FOR RECOGNIZING NATURAL SCENE CATEGORIES

被引：0

作者：

Huu-Giao Nguyen ^{[1
]}

Fablet, Ronan

Boucher, Jean-Marc ^{[2
]}

机构：

[1] Telecom Bretagne, Inst Telecom, LabSTICC, CS 83818, F-29238 Brest 3, France

[2] Univ Europe Bretagne, Bretagne, France

来源：

2011 18TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2011年

关键词：

log-Gaussian Cox process; topographic map; inner-distance shape context; scene recognition;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we address invariant scene classification from images We propose a novel descriptor based on the statistical characterization of the spatial patterns formed by elementary objects in images Elementary objects are defined from a tree of shapes of the topology map of the image and each object is characterized by shape context feature vector. Viewing the set of elementary objects as a realization of a random spatial process, we investigate a statistical analysis using log-Gaussian Cox model to define an invariant image descriptor. An application to natural scene recognition is described. Reported results validate the proposed descriptor with respect to previous work.

引用

页码：665 / 668

页数：4

共 50 条

[1] Visual textures as realizations of multivariate log-Gaussian Cox processes
Huu-Giao Nguyen
Fablet, Ronan
Boucher, Jean-Marc
2011 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2011,
[2] Analysis of multispecies point patterns by using multivariate log-Gaussian Cox processes
Waagepetersen, Rasmus
Guan, Yongtao
Jalilian, Abdollah
Mateu, Jorge
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 2016, 65 (01) : 77 - 96
[3] FAST METHODS FOR FITTING LOG-GAUSSIAN COX PROCESS MODELS IN ECOLOGY
Dovers, Elliot
BULLETIN OF THE AUSTRALIAN MATHEMATICAL SOCIETY, 2023, 107 (02) : 344 - 345
[4] Spatiotemporal prediction for log-Gaussian Cox processes
Brix, A
Diggle, PJ
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2001, 63 : 823 - 841
[5] stelfi: An R package for fitting Hawkes and log-Gaussian Cox point process models
Jones-Todd, Charlotte M.
van Helsdingen, Alec B. M.
ECOLOGY AND EVOLUTION, 2024, 14 (02):
[6] The integrated nested Laplace approximation applied to spatial log-Gaussian Cox process models
Flagg, Kenneth
Hoegh, Andrew
JOURNAL OF APPLIED STATISTICS, 2023, 50 (05) : 1128 - 1151
[7] Local spatial log-Gaussian Cox processes for seismic data
Nicoletta D’Angelo
Marianna Siino
Antonino D’Alessandro
Giada Adelfio
AStA Advances in Statistical Analysis, 2022, 106 : 633 - 671
[8] LOG-GAUSSIAN COX PROCESSES IN INFINITE-DIMENSIONAL SPACES
Torres, A.
Frias, M. P.
Ruiz-Medina, M. D.
THEORY OF PROBABILITY AND MATHEMATICAL STATISTICS, 2016, 95 : 157 - 177
[9] Bayesian Inference and Data Augmentation Schemes for Spatial, Spatiotemporal and Multivariate Log-Gaussian Cox Processes in R
Taylor, Benjamin M.
Davies, Tilman M.
Rowlingson, Barry S.
Diggle, Peter J.
JOURNAL OF STATISTICAL SOFTWARE, 2015, 63 (07): : 1 - 48
[10] On new families of anisotropic spatial log-Gaussian Cox processes
Nasirzadeh, Fariba
Shishebor, Zohreh
Mateu, Jorge
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2021, 35 (02) : 183 - 213

← 1 2 3 4 5 →