Integrating Multiple Sketch Recognition Methods to Improve Accuracy and Speed

Sketch recognition is the computer understanding of hand drawn diagrams. Recognizing sketches instantaneously is necessary to build beautiful interfaces with real time feedback. There are various techniques to quickly recognize sketches into ten or twenty classes. However for much larger datasets of sketches from a large number of classes, these existing techniques can take an extended period of time to accurately classify an incoming sketch and require significant computational overhead. Thus, to make classification of large datasets feasible, we propose using multiple stages of recognition. In the initial stage, gesture-based feature values are calculated and the trained model is used to classify the incoming sketch. Sketches with an accuracy less than a threshold value, go through a second stage of geometric recognition techniques. In the second geometric stage, the sketch is segmented, and sent to shape-specific recognizers. The sketches are matched against predefined shape descriptions, and confidence values are calculated. The system outputs a list of classes that the sketch could be classified as, along with the accuracy, and precision for each sketch. This process both significantly reduces the time taken to classify such huge datasets of sketches, and increases both the accuracy and precision of the recognition

Integrating Multiple Sketch Recognition Methods to Improve Accuracy and Speed

Sketch recognition is the computer understanding of hand drawn diagrams. Recognizing sketches instantaneously is necessary to build beautiful interfaces with real time feedback. There are various techniques to quickly recognize sketches into ten or twenty classes. However for much larger datasets of sketches from a large number of classes, these existing techniques can take an extended period of time to accurately classify an incoming sketch and require significant computational overhead. Thus, to make classification of large datasets feasible, we propose using multiple stages of recognition. In the initial stage, gesture-based feature values are calculated and the trained model is used to classify the incoming sketch. Sketches with an accuracy less than a threshold value, go through a second stage of geometric recognition techniques. In the second geometric stage, the sketch is segmented, and sent to shape-specific recognizers. The sketches are matched against predefined shape descriptions, and confidence values are calculated. The system outputs a list of classes that the sketch could be classified as, along with the accuracy, and precision for each sketch. This process both significantly reduces the time taken to classify such huge datasets of sketches, and increases both the accuracy and precision of the recognition

Knowledge-based systems and geological survey

This personal and pragmatic review of the philosophy underpinning methods of geological surveying suggests that important influences of information technology have yet to make their impact. Early approaches took existing systems as metaphors, retaining the separation of maps, map explanations and information archives, organised around map sheets of fixed boundaries, scale and content. But system design should look ahead: a computer-based knowledge system for the same purpose can be built around hierarchies of spatial objects and their relationships, with maps as one means of visualisation, and information types linked as hypermedia and integrated in mark-up languages. The system framework and ontology, derived from the general geoscience model, could support consistent representation of the underlying concepts and maintain reference information on object classes and their behaviour. Models of processes and historical configurations could clarify the reasoning at any level of object detail and introduce new concepts such as complex systems. The up-to-date interpretation might centre on spatial models, constructed with explicit geological reasoning and evaluation of uncertainties. Assuming (at a future time) full computer support, the field survey results could be collected in real time as a multimedia stream, hyperlinked to and interacting with the other parts of the system as appropriate. Throughout, the knowledge is seen as human knowledge, with interactive computer support for recording and storing the information and processing it by such means as interpolating, correlating, browsing, selecting, retrieving, manipulating, calculating, analysing, generalising, filtering, visualising and delivering the results. Responsibilities may have to be reconsidered for various aspects of the system, such as: field surveying; spatial models and interpretation; geological processes, past configurations and reasoning; standard setting, system framework and ontology maintenance; training; storage, preservation, and dissemination of digital records

Method and Instruments for Modeling Integrated Knowledge

MIMIK (Method and Instruments for Modeling Integrated Knowledge) is a set of tools used to formalize and represent knowledge within organizations. It furthermore supports knowledge creation and sharing within communities of interest or communities of practice. In this paper we show that MIMIK is based on a model theory approach and builds on other existing methods and techniques. We also explain how to use the method and its instruments in order to model strategic objectives, processes, knowledge, and roles found within an organization, as well as relations existing between these elements. Indeed MIMIK provides eight types of models in order to describe what is commonly called know-how, know-why and know-what; it uses matrices in order to formally and semantically link strategic objectives, knowledge and actors. We close this paper with a presentation of a prototype we built in order to demonstrate a technical architecture allowing for knowledge creation, formalization and sharing.knowledge modelling; process modelling; public administration; methodology; knowledge sharing; RSS

UML-F: A Modeling Language for Object-Oriented Frameworks

The paper presents the essential features of a new member of the UML language family that supports working with object-oriented frameworks. This UML extension, called UML-F, allows the explicit representation of framework variation points. The paper discusses some of the relevant aspects of UML-F, which is based on standard UML extension mechanisms. A case study shows how it can be used to assist framework development. A discussion of additional tools for automating framework implementation and instantiation rounds out the paper.Comment: 22 pages, 10 figure

Shape exploration in product design: assisting transformation in pictorial representations

The sketching of pictorial representations forms a key technique for professional designers in the generation and exploration of product shape. It allows ideas of shape to be externalised and communicated, but more importantly, sketched pictorial representations can operate to assist designers' creative thinking. While computer aided design tools have a proven capability to support the development of design ideas, there is still much scope to develop computer based tools that support the free-flowing exploratory thinking that characterises shape generation and shape exploration in product design. Far from being a straight-jacket in creative design, shape rules have significant potential to bridge the gap between traditional sketching techniques and modern computational methods of design. This thesis presents an inquiry into the exploitation of shape rules within product design. It includes studies of design sketches by professional designers and these inform the development of a theoretical model for assisting design transformation. A formal model of exploration is proposed with two mechanisms; shape decomposition and shape transformation. This model is applied using pictorial representations which may be seen as the computing equivalent of freehand sketches, and reveals new strategies for systematic shape generation and exploration in product design

Creating the Perception-based LADDER sketch recognition language

Sketch recognition is automated understanding of hand-drawn diagrams. Current sketch recognition systems exist for only a handful of domains, which contain on the order of 10--20 shapes. Our goal was to create a generalized method for recognition that could work for many domains, increasing the number of shapes that could be recognized in real-time, while maintaining a high accuracy. In an effort to effectively recognize shapes while allowing drawing freedom (both drawing-style freedom and perceptually-valid variations), we created the shape description language modeled after the way people naturally describe shapes to 1) create an intuitive and easy to understand description, providing transparency to the underlying recognition process, and 2) to improve recognition by providing recognition flexibility (drawing freedom) that is aligned with how humans perceive shapes. This paper describes the results of a study performed to see how users naturally describe shapes. A sample of 35 subjects described or drew approximately 16 shapes each. Results show a common vocabulary related to Gestalt grouping and singularities. Results also show that perception, similarity, and context play an important role in how people describe shapes. This study resulted in a language (LADDER) that allows shape recognizers for any domain to be automatically generated from a single hand-drawn example of each shape. Sketch systems for over 30 different domains have been automatically generated based on this language. The largest domain contained 923 distinct shapes, and achieved a recognition accuracy of 83% (and a top-3 accuracy of 87%) on a corpus of over 11,000 sketches, which recognizes almost two orders of magnitude more shapes than any other existing system.National Science Foundation (U.S.) (grant 0757557)National Science Foundation (U.S.) (grant 0943499

The Spatial Nature of Thought: Understanding Systems Design Through Diagrams

Design entails the interaction of minds and the tools used to express the design, notably, diagrams. Systems designers use the affordances of the page when they generate structural diagrams of systems. Specifically, they use proximity to augment connectedness (path) information by grouping subsystems. They use horizontal position on the page to express sequence and vertical position to reflect actual spatial position. Finally, they use the permanence of diagrams to generate alternative designs. These conclusions were reached through the analysis of work by student designers, many of whom were practicing information technology professionals. The analysis of designs in topological and Euclidean space required the creation of computational tools that show promise as decision aids for designers, by separating the intertwined qualities of topological and Euclidean space, and by making visible the conceptual similarity of design alternatives