A Toolbox for Generating Multidimensional 3-D Objects with Fine-Controlled Feature Space: Quaddle 2.0
Wen, X.; Malchin, L. A.; Womelsdorf, T.
Show abstract
Multidimensional 3D-rendered objects are an important component of vision research and video- gaming applications, but it has remained challenging to parametrically control and efficiently generate those objects. Here, we describe a toolbox for controlling and efficiently generating 3D rendered objects composed of ten separate visual feature dimensions that can be fine-adjusted using python scripts. The toolbox defines objects as multi-dimensional feature vectors with primary dimensions (object body related features), secondary dimensions (head related features) and accessory dimensions (including arms, ears, or beaks). The toolkit interfaces with the freely available Blender software to create objects. The toolbox allows to gradually morph features of multiple feature dimensions, determine the desired feature similarity among objects, and automatize the generation of multiple objects in 3D object and 2D image formats. We document the use of multidimensional objects in a sequence learning task that embeds objects in a 3D- rendered augmented reality environment controlled by the gaming engine unity. Taken together, the toolbox enables the efficient generation of multidimensional objects with fine control of low- level features and higher-level object similarity useful for visual cognitive research and immersive visual environments.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- USE: An integrative suite for temporally-precise psychophysical experiments in virtual environments for human, nonhuman, and artificially intelligent agents 97%
- Assessing Attentiveness and Cognitive Engagement across Tasks using Video-based Action Understanding in Non-Human Primates 95%
- NERV: A Comprehensive Framework for Rapid, Reproducible, and Hardware-Synchronized Neuroscience Experiment Design and Execution 95%
Similar papers in this journal
- Measuring motion-to-photon latency for sensorimotor experiments with virtual reality systems 95%
- Towards a standardization of non-symbolic numerical experiments: GeNEsIS, a flexible and user-friendly tool to generate controlled stimuli 95%
- Generating accurate 3D gaze vectors using synchronized eye tracking and motion capture 94%
Similar papers in this journal
- Route selection in non-Euclidean virtual environments 94%
- Influence of open-source virtual-reality based gaze training on navigation performance in Retinitis pigmentosa patients in a crossover randomized controlled trial 93%
- Real-world visual search goes beyond eye movements: Active searchers select 3D scene viewpoints too 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.