The conventional linear model of pedagogical practices promotes subject-centric memorizing, considering learners as knowledge recipients rather than generators knowledge. This practice degrades educational values by ignoring alternative inquiry-based visionaries and meaning-making approaches. Different forms art in pedagogy, such poetry, autobiographical reflection, visual arts (i.e., paintings...

Constructing a distinctive and robust sketch descriptor is one of the most challenging problems in sketch based applications. In this paper, a new hand-drawn sketch descriptor is proposed. The proposed descriptor utilizes the statistic information of multiple features and bag-of-features representation to achieve translation and scale invariance and rotation robustness. The proposed descriptor ...

Hand-drawn sketches are powerful cognitive devices for the efficient exploration, visualization and communication of emerging ideas in engineering design. It is desirable that CAD/CAE tools be able to recognize the back-of-the-envelope sketches and extract the intended engineering models. Yet this is a nontrivial task for freehand sketches. Here we present a novel, neural network-based approach...

Blake Williford Sketch Recognition Lab Texas A&M University [email protected] Wayne Li School of Industrial Design Georgia Institute of Technology [email protected] Ethan Hilton iDREEM Lab Georgia Institute of Technology [email protected] Julie Linsey iDREEM Lab Georgia Institute of Technology [email protected] Tracy Hammond Sketch Recognition Lab Texas A&M University tham...

The evaluation of a patient’s drawing abilities is widely used for the diagnosis of neuropsychological conditions such as visuo-spatial neglect. Conventionally an analysis of simple constructional tasks such as pencil and paperbased drawing tests are analysed by a qualified medical specialist. However, variability in the assessment of these drawing tasks caused by the subjective nature of marki...

We describe a novel method of evolutionary visual learning that uses generative approach for assessing learner’s ability to recognize image contents. Each learner, implemented as a genetic programming individual, processes visual primitives that represent local salient features derived from a raw input raster image. In response to that input, the learner produces partial reproduction of the inp...

In this paper, we present a new feature extraction technique and a novel Hidden Markov Model (HMM) based classifier for the rotation, translation and scale invariant recognition of handdrawn pictograms. The feature extraction is performed by taking a fixed dimensional vector along the radius of a circle surrounding the pictogram. Within the HMM-framework these features are used to classify the ...

In the field of Computational Geometry, the design of 3D models using hand drawn strokes has been well-studied in recent years as a way to improve user interfaces. When using hand-drawn strokes to design 3D models, an algorithm for cutting a model by a stroke is required. Previous algorithms have concentrated on precision and are expensive to implement. This paper gives priority to simplicity a...

A method for automatically assessing the constructional sequence from a neuropsychological drawing task using Hidden Markov Models is presented. We also present a method of extracting and identifying the position of individual pen strokes relating to individual sides of a shape within a drawing to form training and testing sequences. Our results from two experiments using data from patients wit...