5 research outputs found
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
Information visualization: from petroglyphs to CoDe Graphs
2016 - 2017Data visualization concerns the communication of data through visual representations and
techniques. It aims at enhancing perception and support data-driven decision making so
enabling insights otherwise hard to achieve. A good visualization of data makes it possible
to identify patterns and enables better understanding of phenomena. In other words, data
visualization is related to an innate human ability to quickly comprehend, discern and
convert patterns into useful and usable information.
Humans have used visual graphical representations as early as 35.000 B.C., through
cave drawings. Indeed, human ancestors already reasoned in terms of models or schemata:
the visual representation of information is an ancient concept, as witnessed by the rock
carvings found. Over the centuries, information visualization has evolved to take into
account the changing human needs and its use has become more and more conscious. The
first data visualization techniques have been developed to observe and represent physical
quantities, geography and celestial positions. Successively, the combined use of euclidean
geometry and algebra improved accuracy and complexity of information representation, in
different fields, such as astronomy, physics and engineering. Finally, in the last century
most modern forms of data representations were invented: starting from charts, histograms,
and graphs up to high dimensional data, and dynamic and interactive visualizations of
temporal data [41].
Nowadays, the huge amount of information enables more precise interpretation of phenomena
so fostering the adoption of infographic techniques, in particular, for supporting
managerial decision-making in the business area... [edited by author]XVI n.s
An agent-based framework for sketched symbol interpretation
Recognizing hand-sketched symbols is a definitely complex problem. The input drawings are often intrinsically ambiguous, and require context to be interpreted in a correct way. Many existing sketch recognition systems avoid this problem by recognizing single segments or simple geometric shapes in a stroke. However, for a recognition system to be effective and precise, context must be exploited, and both the simplifications on the sketch features, and the constraints under which recognition may take place, must be reduced to the minimum.
In this paper, we present an agent-based framework for sketched symbol interpretation that heavily exploits contextual information for ambiguity resolution. Agents manage the activity of low- level hand-drawn symbol recognizers, that may be heterogeneous for better adapting to the characteristics of each symbol to be recognized, and coordinate themselves in order to exchange contextual information, thus leading to an efficient and precise interpretation of sketches. We also present AgentSketch, a multi-domain sketch recognition system implemented according to the proposed framework. A first experimental evaluation has been performed on the domain of UML Use Case Diagrams to verify the effectiveness of the proposed approach
New methods, techniques and applications for sketch recognition
2012-2013The use of diagrams is common in various disciplines. Typical examples
include maps, line graphs, bar charts, engineering blueprints, architects’
sketches, hand drawn schematics, etc.. In general, diagrams can be created
either by using pen and paper, or by using specific computer programs. These
programs provide functions to facilitate the creation of the diagram, such as
copy-and-paste, but the classic WIMP interfaces they use are unnatural when
compared to pen and paper. Indeed, it is not rare that a designer prefers
to use pen and paper at the beginning of the design, and then transfer the
diagram to the computer later.
To avoid this double step, a solution is to allow users to sketch directly on
the computer. This requires both specific hardware and sketch recognition
based software. As regards hardware, many pen/touch based devices such as
tablets, smartphones, interactive boards and tables, etc. are available today,
also at reasonable costs. Sketch recognition is needed when the sketch must
be processed and not considered as a simple image and it is crucial to the
success of this new modality of interaction. It is a difficult problem due to the
inherent imprecision and ambiguity of a freehand drawing and to the many
domains of applications. The aim of this thesis is to propose new methods
and applications regarding the sketch recognition. The presentation of the
results is divided into several contributions, facing problems such as corner
detection, sketched symbol recognition and autocompletion, graphical context
detection, sketched Euler diagram interpretation.
The first contribution regards the problem of detecting the corners present
in a stroke. Corner detection is often performed during preprocessing to
segment a stroke in single simple geometric primitives such as lines or curves.
The corner recognizer proposed in this thesis, RankFrag, is inspired by the
method proposed by Ouyang and Davis in 2011 and improves the accuracy
percentages compared to other methods recently proposed in the literature.
The second contribution is a new method to recognize multi-stroke hand
drawn symbols, which is invariant with respect to scaling and supports symbol
recognition independently from the number and order of strokes. The method
is an adaptation of the algorithm proposed by Belongie et al. in 2002 to the
case of sketched images. This is achieved by using stroke related information.
The method has been evaluated on a set of more than 100 symbols from
the Military Course of Action domain and the results show that the new
recognizer outperforms the original one.
The third contribution is a new method for recognizing multi-stroke partially
hand drawn symbols which is invariant with respect to scale, and
supports symbol recognition independently from the number and order of
strokes. The recognition technique is based on subgraph isomorphism and
exploits a novel spatial descriptor, based on polar histograms, to represent
relations between two stroke primitives. The tests show that the approach
gives a satisfactory recognition rate with partially drawn symbols, also with
a very low level of drawing completion, and outperforms the existing approaches
proposed in the literature. Furthermore, as an application, a system
presenting a user interface to draw symbols and implementing the proposed
autocompletion approach has been developed. Moreover a user study aimed
at evaluating the human performance in hand drawn symbol autocompletion
has been presented. Using the set of symbols from the Military Course of
Action domain, the user study evaluates the conditions under which the
users are willing to exploit the autocompletion functionality and those under
which they can use it efficiently. The results show that the autocompletion
functionality can be used in a profitable way, with a drawing time saving of
about 18%.
The fourth contribution regards the detection of the graphical context of
hand drawn symbols, and in particular, the development of an approach for
identifying attachment areas on sketched symbols. In the field of syntactic
recognition of hand drawn visual languages, the recognition of the relations
among graphical symbols is one of the first important tasks to be accomplished
and is usually reduced to recognize the attachment areas of each symbol and
the relations among them. The approach is independent from the method used
to recognize symbols and assumes that the symbol has already been recognized.
The approach is evaluated through a user study aimed at comparing the
attachment areas detected by the system to those devised by the users. The
results show that the system can identify attachment areas with a reasonable
accuracy.
The last contribution is EulerSketch, an interactive system for the sketching
and interpretation of Euler diagrams (EDs). The interpretation of a hand
drawn ED produces two types of text encodings of the ED topology called
static code and ordered Gauss paragraph (OGP) code, and a further encoding
of its regions. Given the topology of an ED expressed through static or OGP
code, EulerSketch automatically generates a new topologically equivalent ED
in its graphical representation. [edited by author]XII n.s
Pen-based Methods For Recognition and Animation of Handwritten Physics Solutions
There has been considerable interest in constructing pen-based intelligent tutoring systems due to the natural interaction metaphor and low cognitive load afforded by pen-based interaction. We believe that pen-based intelligent tutoring systems can be further enhanced by integrating animation techniques. In this work, we explore methods for recognizing and animating sketched physics diagrams. Our methodologies enable an Intelligent Tutoring System (ITS) to understand the scenario and requirements posed by a given problem statement and to couple this knowledge with a computational model of the student\u27s handwritten solution. These pieces of information are used to construct meaningful animations and feedback mechanisms that can highlight errors in student solutions. We have constructed a prototype ITS that can recognize mathematics and diagrams in a handwritten solution and infer implicit relationships among diagram elements, mathematics and annotations such as arrows and dotted lines. We use natural language processing to identify the domain of a given problem, and use this information to select one or more of four domain-specific physics simulators to animate the user\u27s sketched diagram. We enable students to use their answers to guide animation behavior and also describe a novel algorithm for checking recognized student solutions. We provide examples of scenarios that can be modeled using our prototype system and discuss the strengths and weaknesses of our current prototype. Additionally, we present the findings of a user study that aimed to identify animation requirements for physics tutoring systems. We describe a taxonomy for categorizing different types of animations for physics problems and highlight how the taxonomy can be used to define requirements for 50 physics problems chosen from a university textbook. We also present a discussion of 56 handwritten solutions acquired from physics students and describe how suitable animations could be constructed for each of them