IQmulus Processing Contest 2016
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IQmulus Processing Contests
The objective of the IQmulus Processing Contest (IQPC) is to evaluate the performance of software developed for geospatial data processing, an area which requires expertise from various disciplines: Geometry Processing, Computer Vision, Remote Sensing and Geomatics.
Examples of geospatial processing tasks are the registration and alignment of heterogeneous point clouds, the classification and extraction of features in spatial datasets, the detection and characterization of dynamic events acquired by remote sensing or LiDAR techniques.
Programs performance is evaluated through the creation of benchmarks and evaluation methodologies specific for selected processing tasks (IQmulus tracks). Besides the selection of test datasets with a ground truth, IQPC supports the usage of a common infrastructure where the executables submitted are run and results collected and evaluated. For this purpose both WINDOWS and Linux virtual machines will be set up.
IQmulus Processing Contest 2015
Since 2013, IQPC is featured by the EU
IQmulus project and encourages the participation of the whole scientific community as well as specific user groups. This year, IQPC 2015 will be the theme of a Special Session in the ISPRS GeoBigData conference and track reports will be reviewed to be included in the conference proceedings.
GeoBigData - ISPRS Geospatial Week (Montpellier (La Grande Motte), France, 28. september - 01. october 2015.)
IQmulus Processing Contest 2014
Since 2013, IQmulus and encourages the participation of the whole scientific community to the evaluation of algorithms and software developed for processing geospatial data. The results of the contest were presented at the Workshop on Processing Large Geospatial Data, organized as a co-located event of the Eurographics Symposium on Geometry Processing 2014, Cardiff, July 7-11 2014.
IQmulus Processing Contest 2013
An initiative similar to the IQmulus processing contest has started in 2011 under the aegis of the ISPRS (Rottensteiner et al., 2012). The need of new standard test sites that exploit the availability of modern airborne sensors led to the creation of a benchmark on urban object extraction. In particular, both airborne topographic Lidar data and multi‐view stereo imagery are provided to compare and evaluate research algorithms for building detection, tree detectionand building reconstruction in urban areas. In addition, a benchmark dataset on shape registration has been recently proposed in the field of robotic research (Pomerleau et al.,2013). The results of the contest highlighted that there is still place for further developments in all the scenarios considered; in particular the detection of small building structures and trees and the production of high‐quality level‐of‐detail building models. As a further outcome, the methods currently at the state of the art do not seem to be able to fully exploit the accuracy potential inherent in the sensor data.