A new paradigm based on agents applied to free-hand sketch recognition

Important advances in natural calligraphic interfaces for CAD (Computer Aided Design) applications are being achieved, enabling the development of CAS (Computer Aided Sketching) devices that allow facing up to the conceptual design phase of a product. Recognizers play an important role in this field, allowing the interpretation of the user’s intention, but they still present some important lacks. This paper proposes a new recognition paradigm using an agent-based architecture that does not depend on the drawing sequence and takes context information into account to help decisions. Another improvement is the absence of operation modes, that is, no button is needed to distinguish geometry from symbols or gestures, and also “interspersing” and “overtracing” are accomplishedThe Spanish Ministry of Science and Education and the FEDER Funds, through the CUESKETCH project (Ref. DPI2007-66755-C02-01), partially supported this work.Fernández Pacheco, D.; Albert Gil, FE.; Aleixos Borrás, MN.; Conesa Pastor, J. (2012). A new paradigm based on agents applied to free-hand sketch recognition. Expert Systems with Applications. 39(8):7181-7195. https://doi.org/10.1016/j.eswa.2012.01.063S7181719539

A new agent-based paradigm for recognition of free-hand sketches

AbstractCurrently, important advances are carried out in CAD (Computer Aided Design) applications; however these advances have not taken place for CAS (Computer Aided Sketching) applications. Although natural interfaces for CAD applications are not solved yet, works based on sketching devices have been explored to some extent. The recognition paradigm we propose using an agentbased architecture does not depend on the drawing sequence and takes context information into account to help decisions. An improvement provided is the absence of operation modes, that is, no button is needed to distinguish geometry from symbols or gestures, and also “interspersing” and “overtracing” is accomplished

Attention based detection and recognition of hand postures against complex backgrounds

10.1007/s11263-012-0560-5International Journal of Computer Vision1013403-419IJCV