jjponciano / knowdip

The "Knowledge-based object Detection in Image and Point cloud" (KnowDIP) project aims at the conception of a framework for automatic object detection in unstructured and heterogeneous data. This framework uses a representation of human knowledge in order to improve the flexibility, accuracy, and efficiency of data processing.

Knowledge-based object Detection in Image and Point cloud (KnowDIP)

knowdip is a project of the institute i3mainz

Instalation

knowdip needs libraries to work including JavaPointCloud. Being entirely written in java, the easiest way to install it is to use MAVEN. To do so, install MAVEN by following the instructions given here.

Then clone or download the source code, go to the directory where the "pom.xml" file is located and execute the following command in a terminal:

mvn install

The same process must first be performed on the JavaPointCloud library on which knowdip depends.

Conditions of use:

The user of this project must insert the following citation in any scientific or technical publication whenever the framework or a part its source code was used:

Ponciano, Jean-Jacques, Alain Trémeau, and Frank Boochs. "Automatic Detection of Objects in 3D Point Clouds Based on Exclusively Semantic Guided Processes." ISPRS International Journal of Geo-Information 8.10 (2019): 442.

Publications:

Jean-Jacques Ponciano, Frank Boochs, Alain Trémeau. 3D object recognition through a process based on semantics and consideration of the context. Photogrammetrie, Laserscanning, Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2020, 2020. ⟨hal-02651917⟩

Ponciano, Jean-Jacques, Alain Trémeau, and Frank Boochs. "Automatic Detection of Objects in 3D Point Clouds Based on Exclusively Semantic Guided Processes." ISPRS International Journal of Geo-Information 8.10 (2019): 442.

Jean-Jacques Ponciano. Object detection in unstructured 3D data sets using explicit semantics. Artificial Intelligence [cs.AI]. Université de Lyon, 2019. English. ⟨NNT : 2019LYSES059⟩. ⟨tel-02497452⟩

Ponciano JJ., Karmacharya A., Wefers S., Atorf P., Boochs F. (2019) Connected Semantic Concepts as a Base for Optimal Recording and Computer-Based Modelling of Cultural Heritage Objects. In: Aguilar R., Torrealva D., Moreira S., Pando M.A., Ramos L.F. (eds) Structural Analysis of Historical Constructions. RILEM Bookseries, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-319-99441-3_31

Jean-Jacques Ponciano, Frank Boochs, Alain Tremeau. Identification and classification of objects in 3D point clouds based on a semantic concept. 3D-Tage, Feb 2019, Oldenburger, Germany. ⟨hal-02014831⟩

Jean-Jacques Ponciano, Frank Boochs, Trémeau Alain. Knowledge-based object recognition in point clouds and image data sets. gis.Science - Die Zeitschrift für Geoinformatik, Wichmann, 2017. ⟨hal-02047375⟩

knowdip's Issues

redundancy in the parameters of the knowdip functions

Var parameter for displaying could be replaced by the function getSparqlVar