Add to ORKGClassifying and gathering additional information about an unknown 3D objects is dependent on having a large amount of learning data. We propose to use procedural models as data foundation for this task. In our method we (semi-)automatically define parameters for a procedural model constructed with a modeling tool. Then we use the procedural models to classify an object and also automatically estimate the best parameters. We use a standard convolutional neural network and three different object similarity measures to estimate the best parameters at each degree of detail. We evaluate all steps of our approach using several procedural models and show that we can achieve high classification accuracy and meaningful parameters for unknown objects
To endow machines with the ability to perceive the real-world in a three dimensional representation ...
Procedural modeling techniques can be used to encode a geometric shape on a high and abstract level:...
Digital representations of 3D shapes are becoming increasingly useful in several emerging applicatio...
Classifying and gathering additional information about an unknown 3D objects is dependent on having ...
The amount of 3D objects has grown over the last decades, but we can expect that it will grow much f...
3D Object Classification Using Neural Networks Bc. Miroslav Krabec Classification of 3D objects is o...
We propose parametric geons as a coarse description of object components for qualitative object reco...
Deep learning-based object detection and pose estimation methods need a large number of synthetic da...
Robots are mechanically capable of doing many tasks, carrying loads, precisely manipulating objects,...
3D objects are used for numerous applications. In many cases not only single objects but also variat...
We analyze the amount of information needed to carry out model-based recognition tasks, in the conte...
Procedural modeling techniques can be used to encode a geometric shape on a high and abstract level:...
A new approach for computing qualitative part-based descriptions of 3D objects from single- and mult...
In this work, we propose the implementation of a 3D object recognition system using Convolutional Ne...
A desirable 3D model classification system should be equipped with qualities such as highly correct ...
To endow machines with the ability to perceive the real-world in a three dimensional representation ...
Procedural modeling techniques can be used to encode a geometric shape on a high and abstract level:...
Digital representations of 3D shapes are becoming increasingly useful in several emerging applicatio...
Classifying and gathering additional information about an unknown 3D objects is dependent on having ...
The amount of 3D objects has grown over the last decades, but we can expect that it will grow much f...
3D Object Classification Using Neural Networks Bc. Miroslav Krabec Classification of 3D objects is o...
We propose parametric geons as a coarse description of object components for qualitative object reco...
Deep learning-based object detection and pose estimation methods need a large number of synthetic da...
Robots are mechanically capable of doing many tasks, carrying loads, precisely manipulating objects,...
3D objects are used for numerous applications. In many cases not only single objects but also variat...
We analyze the amount of information needed to carry out model-based recognition tasks, in the conte...
Procedural modeling techniques can be used to encode a geometric shape on a high and abstract level:...
A new approach for computing qualitative part-based descriptions of 3D objects from single- and mult...
In this work, we propose the implementation of a 3D object recognition system using Convolutional Ne...
A desirable 3D model classification system should be equipped with qualities such as highly correct ...
To endow machines with the ability to perceive the real-world in a three dimensional representation ...
Procedural modeling techniques can be used to encode a geometric shape on a high and abstract level:...
Digital representations of 3D shapes are becoming increasingly useful in several emerging applicatio...