Sketch recognition

About: Sketch recognition is a research topic. Over the lifetime, 1611 publications have been published within this topic receiving 40284 citations.

An on-line sketch recognition algorithm for composite shape

Abstract: Existing sketch recognition algorithms are mainly on recognizing single segments or simple geometric objects (such as rectangles) in a stroke. We present in this paper an on-line sketch recognition algorithm for composite shapes. It can recognize single shape segments such as straight line, polygon, circle, circular arc, ellipse, elliptical arc, hyperbola, and parabola curves in a stroke, as well as any composition of these segments in a stroke. Our algorithm first segments the stroke into multi-segments based on a key point detection algorithm. Then we use “combination” fitting method to fit segments in sequence iteratively. The algorithm is already incorporated into a hand sketching based modeling prototype, and experiments show that our algorithm is efficient and well suited for real time on-line applications.

Concepts for automated pattern recognition research with hybrid optical/digital systems

Abstract: Concepts for automated pattern recognition research with hybrid optical/digital systems are discussed for application to present and future mapping and terrain intelligence tasks. Optical and digital pattern recognition approaches which may contribute to hybrid techniques are outlined and a generalized hybrid system model introduces system components, their roles and their interfaces. The automated pattern recognition research program at USAETL, which mainly involves optical power spectral analysis, is sketched for applications research, new approaches, and integration of pattern recognition systems. The paper concludes with estimates of the present state of automated hybrid optical/digital pattern recognition that point to research areas for developing viable systems of the future.

Dressing and hair-styling virtual characters from a sketch

Abstract: This chapter presents a different use of sketch-based modeling, namely the modeling of complex objects from a single sketch, illustrated by the examples of dressing and hairstyling a virtual character. Knowing the nature of the object being modeled eases the extraction of information from a sketch, so that a single sketch depicting a front view (and optionally a second one from the back or side) is sufficient to specify these complex 3D shapes. We show how different levels of prior knowledge about the object being modeled, from basic rules of thumb to more intricate geometric or physically based properties, can be used to interpret the sketch strokes and to infer the missing 3D information, leading to different degrees of visual realism. In addition to discussing practical solutions for the sketch-based modeling of garments and hair that save several orders of magnitude of user time compared to standard 3D modeling methods, this chapter provides the basis of a general methodology towards the design of sketch-based interfaces for complex models.

Workshop - integrating sketch recognition technologies into your classroom

Abstract: Graphical diagrams are an important part of the educational process, as students draw diagrams in fields as various as business, math, computer science, engineering, music, and many others. Hand-sketched student diagrams aid in active learning and creative processes. However, correcting hand-sketch diagrams take a significant amount of teacher time, and are thus often left out of the testing process. Automatically correcting these diagrams can provide immediate student and instructor feedback while significantly reducing instructor time. This workshop will introduce the audience to sketch recognition tools that are available for use in their classroom for active learning, immediate feedback, and automated assessment.