Groupwise Registration of Aerial Images
Authors: Ognjen Arandjelovic, Duc-Son Pham, Svetha Venkatesh
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this section we describe our evaluation of the proposed method, and report and discuss its performance in the context of the current state-of-the-art. We begin by describing our data set and evaluation protocol, follow with a presentation of a comprehensive set of performance statistics, and finish off with an analysis of our results and their significance. |
| Researcher Affiliation | Academia | Centre for Pattern Recognition & Data Analytics Department of Computing Deakin University, Australia Curtin University, Australia |
| Pseudocode | No | The paper describes the proposed approach and its steps in detail using textual explanations and mathematical equations, but it does not include a formal pseudocode block or algorithm box. |
| Open Source Code | No | The paper does not provide any explicit statements about releasing source code or links to a code repository for the described methodology. |
| Open Datasets | No | It is an unsurprising consequence of this that there are no public data sets suitable for the evaluation of set-based algorithms so we collected a novel data set ourselves. Our data set comprises 10 image sets, each set containing 10 images acquired at different, non-uniformly distributed dates, as illustrated in Fig 5. This data was manually downloaded using the freely accessible web portal provided by Nearmap Ltd. |
| Dataset Splits | No | The paper mentions collecting a novel dataset and using 10 image sets, each containing 10 images, and also evaluates |
| Hardware Specification | Yes | The estimates are averages of 100 executions ran in Matlab 7 on an AMD Phenom II X4 965 processor with 8GB RAM. |
| Software Dependencies | Yes | ARRSI and the SURF-based methods were implemented primarily in C, with a Matlab wrapper , while the proposed method was implemented fully in Matlab. The estimates are averages of 100 executions ran in Matlab 7 on an AMD Phenom II X4 965 processor with 8GB RAM. |
| Experiment Setup | Yes | The particular filters we used in our experiments have the values of 40, 20, 8, and 3 pixels for the parameter σ in (7). |