This contest involved the running and evaluation of computer vision and pattern recognition techniques on different data sets with known groundwidth. The contest included three areas; binary shape recognition, symbol recognition and image flow estimation. A package was made available for each area. Each package contained either real images with manual groundtruth or programs to generate data sets of ideal as well as noisy images with known groundtruth. They also contained programs to evaluate the results of an algorithm according to the given groundtruth. These evaluation criteria included the generation of confusion matrices, computation of the misdetection and false alarm rates and other performance measures suitable for the problems. The...
Developments in machine learning in recent years have created opportunities that previously never ex...
To develop an algorithm for an image processing task a person normally should have both extensive ex...
Current research in the area of automatic visual object recognition heavily relies on testing the pe...
This contest involved the running and evaluation of computer vision and pattern recognition techniqu...
This contest involved the running and evaluation of com-puter vision and pattern recognition techniq...
Image processing technology is used in everyday applications to do things such as correct red-eye in...
Until now there have been few formalized methods for conducting systematic benchmarking aiming at re...
Abstract. This paper defines a computational protocol for evaluating the performance of raster to ve...
A big part of computer vision concerns the issue ofhow well images can be classified into their corr...
It is frequently remarked that designers of computer vision algorithms and systems cannot reliably p...
The background, development, performance assessment, and analysis of a novel pattern recognition alg...
Abstract- We present a methodology for the quantitative performance evaluation of detection algorith...
In the context of virtual and augmented reality, computer vision plays a pivotal role. To benchmark ...
International audienceEvaluation of object detection algorithms is a non-trivial task: a detection r...
The paper highlights approaches to reference data acquisition in real environments for the purpose o...
Developments in machine learning in recent years have created opportunities that previously never ex...
To develop an algorithm for an image processing task a person normally should have both extensive ex...
Current research in the area of automatic visual object recognition heavily relies on testing the pe...
This contest involved the running and evaluation of computer vision and pattern recognition techniqu...
This contest involved the running and evaluation of com-puter vision and pattern recognition techniq...
Image processing technology is used in everyday applications to do things such as correct red-eye in...
Until now there have been few formalized methods for conducting systematic benchmarking aiming at re...
Abstract. This paper defines a computational protocol for evaluating the performance of raster to ve...
A big part of computer vision concerns the issue ofhow well images can be classified into their corr...
It is frequently remarked that designers of computer vision algorithms and systems cannot reliably p...
The background, development, performance assessment, and analysis of a novel pattern recognition alg...
Abstract- We present a methodology for the quantitative performance evaluation of detection algorith...
In the context of virtual and augmented reality, computer vision plays a pivotal role. To benchmark ...
International audienceEvaluation of object detection algorithms is a non-trivial task: a detection r...
The paper highlights approaches to reference data acquisition in real environments for the purpose o...
Developments in machine learning in recent years have created opportunities that previously never ex...
To develop an algorithm for an image processing task a person normally should have both extensive ex...
Current research in the area of automatic visual object recognition heavily relies on testing the pe...