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

Mereological nihilism: quantum atomism and the impossibility of material constitution

Mereological nihilism is the philosophical position that there are no items that have parts. If there are no items with parts then the only items that exist are partless fundamental particles, such as the true atoms (also called philosophical atoms) theorized to exist by some ancient philosophers, some contemporary physicists, and some contemporary philosophers. With several novel arguments I show that mereological nihilism is the correct theory of reality. I will also discuss strong similarities that mereological nihilism has with empirical results in quantum physics. And I will discuss how mereological nihilism vindicates a few other theories, such as a very specific theory of philosophical atomism, which I will call quantum abstract atomism. I will show that mereological nihilism also is an interpretation of quantum mechanics that avoids the problems of other interpretations, such as the widely known, metaphysically generated, quantum paradoxes of quantum physics, which ironically are typically accepted as facts about reality. I will also show why it is very surprising that mereological nihilism is not a widely held theory, and not the premier theory in philosophy

3D-Scanner for Hochschule Esslingen

The work was done for Hochschule Esslingen and its main purpose was to provide the school with a comprehensive explanation of different 3-dimensional scanning systems and their functions. It was also deemed necessary for it to provide reviews of dimensional scanning equipment on the market with a detailed review of at least one system, as well as provide arguments to why the School should obtain the technology as a part of its process chain. The research was done using the internet to search for different sources such as technology reviews, news articles and books sources as well as blogs and forums where enthusiasts talk about the subject matter. Finally, a free photogrammetry app was downloaded from the app store for practical review purposes. The result of the research is a broad review of the current technology and what are considered the most eligible commercial scanners through different criteria’s such as price, ease of use and accuracy, with some speculation of the future of the technology and its benefits

A Fine Motor Skill Classifying Framework to Support Children's Self-Regulation Skills and School Readiness

Children’s self-regulation skills predict their school-readiness and social behaviors, and assessing these skills enables parents and teachers to target areas for improvement or prepare children to enter school ready to learn and achieve. Assessing these skills enables parents and teachers to target areas for improvement or prepare children to enter school ready to learn and achieve. To assess children’s fine motor skills, current educators are assessing those skills by either determining their shape drawing correctness or measuring their drawing time durations through paper-based assessments. However, the methods involve human experts manually assessing children’s fine motor skills, which are time consuming and prone to human error and bias. As there are many children that use sketch-based applications on mobile and tablet devices, computer-based fine motor skill assessment has high potential to solve the limitations of the paper-based assessments. Furthermore, sketch recognition technology is able to offer more detailed, accurate, and immediate drawing skill information than the paper-based assessments such as drawing time or curvature difference. While a number of educational sketch applications exist for teaching children how to sketch, they are lacking the ability to assess children’s fine motor skills and have not proved the validity of the traditional methods onto tablet-environments. We introduce our fine motor skill classifying framework based on children’s digital drawings on tablet-computers. The framework contains two fine motor skill classifiers and a sketch-based educational interface (EasySketch). The fine motor skill classifiers contain: (1) KimCHI: the classifier that determines children’s fine motor skills based on their overall drawing skills and (2) KimCHI2: the classifier that determines children’s fine motor skills based on their curvature- and corner-drawing skills. Our fine motor skill classifiers determine children’s fine motor skills by generating 131 sketch features, which can analyze their drawing ability (e.g. DCR sketch feature can determine their curvature-drawing skills). We first implemented the KimCHI classifier, which can determine children’s fine motor skills based on their overall drawing skills. From our evaluation with 10- fold cross-validation, we found that the classifier can determine children’s fine motor skills with an f-measure of 0.904. After that, we implemented the KimCHI2 classifier, which can determine children’s fine motor skills based on their curvature- and corner-drawing skills. From our evaluation with 10-fold cross-validation, we found that the classifier can determine children’s curvature-drawing skills with an f-measure of 0.82 and corner-drawing skills with an f-measure of 0.78. The KimCHI2 classifier outperformed the KimCHI classifier during the fine motor skill evaluation. EasySketch is a sketch-based educational interface that (1) determines children’s fine motor skills based on their drawing skills and (2) assists children how to draw basic shapes such as alphabet letters or numbers based on their learning progress. When we evaluated our interface with children, our interface determined children’s fine motor skills more accurately than the conventional methodology by f-measures of 0.907 and 0.744, accordingly. Furthermore, children improved their drawing skills from our pedagogical feedback. Finally, we introduce our findings that sketch features (DCR and Polyline Test) can explain children’s fine motor skill developmental stages. From the sketch feature distributions per each age group, we found that from age 5 years, they show notable fine motor skill development

Rethinking Pen Input Interaction: Enabling Freehand Sketching Through Improved Primitive Recognition

Online sketch recognition uses machine learning and artificial intelligence techniques to interpret markings made by users via an electronic stylus or pen. The goal of sketch recognition is to understand the intention and meaning of a particular user's drawing. Diagramming applications have been the primary beneficiaries of sketch recognition technology, as it is commonplace for the users of these tools to rst create a rough sketch of a diagram on paper before translating it into a machine understandable model, using computer-aided design tools, which can then be used to perform simulations or other meaningful tasks. Traditional methods for performing sketch recognition can be broken down into three distinct categories: appearance-based, gesture-based, and geometric-based. Although each approach has its advantages and disadvantages, geometric-based methods have proven to be the most generalizable for multi-domain recognition. Tools, such as the LADDER symbol description language, have shown to be capable of recognizing sketches from over 30 different domains using generalizable, geometric techniques. The LADDER system is limited, however, in the fact that it uses a low-level recognizer that supports only a few primitive shapes, the building blocks for describing higher-level symbols. Systems which support a larger number of primitive shapes have been shown to have questionable accuracies as the number of primitives increase, or they place constraints on how users must input shapes (e.g. circles can only be drawn in a clockwise motion; rectangles must be drawn starting at the top-left corner). This dissertation allows for a significant growth in the possibility of free-sketch recognition systems, those which place little to no drawing constraints on users. In this dissertation, we describe multiple techniques to recognize upwards of 18 primitive shapes while maintaining high accuracy. We also provide methods for producing confidence values and generating multiple interpretations, and explore the difficulties of recognizing multi-stroke primitives. In addition, we show the need for a standardized data repository for sketch recognition algorithm testing and propose SOUSA (sketch-based online user study application), our online system for performing and sharing user study sketch data. Finally, we will show how the principles we have learned through our work extend to other domains, including activity recognition using trained hand posture cues

Eye Tracking Methods for Analysis of Visuo-Cognitive Behavior in Medical Imaging

Predictive modeling of human visual search behavior and the underlying metacognitive processes is now possible thanks to significant advances in bio-sensing device technology and machine intelligence. Eye tracking bio-sensors, for example, can measure psycho-physiological response through change events in configuration of the human eye. These events include positional changes such as visual fixation, saccadic movements, and scanpath, and non-positional changes such as blinks and pupil dilation and constriction. Using data from eye-tracking sensors, we can model human perception, cognitive processes, and responses to external stimuli. In this study, we investigated the visuo-cognitive behavior of clinicians during the diagnostic decision process for breast cancer screening under clinically equivalent experimental conditions involving multiple monitors and breast projection views. Using a head-mounted eye tracking device and a customized user interface, we recorded eye change events and diagnostic decisions from 10 clinicians (three breast-imaging radiologists and seven Radiology residents) for a corpus of 100 screening mammograms (comprising cases of varied pathology and breast parenchyma density). We proposed novel features and gaze analysis techniques, which help to encode discriminative pattern changes in positional and non-positional measures of eye events. These changes were shown to correlate with individual image readers' identity and experience level, mammographic case pathology and breast parenchyma density, and diagnostic decision. Furthermore, our results suggest that a combination of machine intelligence and bio-sensing modalities can provide adequate predictive capability for the characterization of a mammographic case and image readers diagnostic performance. Lastly, features characterizing eye movements can be utilized for biometric identification purposes. These findings are impactful in real-time performance monitoring and personalized intelligent training and evaluation systems in screening mammography. Further, the developed algorithms are applicable in other application domains involving high-risk visual tasks

Recognizing Seatbelt-Fastening Behavior with Wearable Technology and Machine Learning

In the case of many fatal automobile accidents, the victims were found to have not been wearing a seatbelt. This occurs in spite of the numerous safety sensors and warning indicators embedded within modern vehicles. Indeed, there is yet room for improvement in terms of seatbelt adoption. This work aims to lay the foundation for a novel method of encouraging seatbelt use: the utilization of wearable technology. Wearable technology has enabled considerable advances in health and wellness. Specifically, fitness trackers have achieved widespread popularity for their ability to quantify and analyze patterns of physical activity. Thanks to wearable technology’s ease of use and convenient integration with mobile phones, users are quick to adopt. Of course, the practicality of wearable technology depends on activity recognition—the models and algorithms which are used to identify a pattern of sensor data as a particular physical activity (e.g. running, sitting, sleeping). Activity recognition is the basis of this research. In order to utilize wearable trackers toward the cause of seatbelt usage, there must exist a system for identifying whether a user has buckled their seatbelt. This was our primary goal. To develop such a system, we collected motion data from 20 different users. From this data, we identified trends which inspired the development of novel features. With these features, machine learning was used to train models to identify the motion of fastening a seatbelt in real time. This model serves as the basis for future work in systems which may provide more intelligent feedback as well as methods for interventions in dangerous user behavior

Rendering Differentials: Introjective Architecture In The Age Of The Digital

Abstract This paper begins by probing the ambivalent and frequently conflicting relation between “architecture” and “picture”. The polemic of forms and techniques of representation imposing its order upon the nature of architectural production is debated in relation to forces of technological transformations driven by more profound cultural imperatives. There had been a persistent divide between the projective and the pictorial in the discipline of architecture in Western tradition from C15th to late C20th. The divide is still evident at the time of the spread of digital technology in design practice since 1980s, when vector graphics took on the task of projective elaboration and raster graphics dealt with pictorial manipulation. However, by the turn of the C21st, a particular capability of digital inter-convertibility led to the incidental dissolution of the divide and the end of the projective dominance. Rendering technology returns the visualising process to the perception-based “image of substance”. And at the same time the experimentation of force-dependent animate form is hinged upon the ability of visualizise differential calculations rapidly. The final part speculates on growing tendencies of pictorial materialisation and effect engineering as part of a different model of architectural production which can be called “introjective”.  Resumen Este ensayo inicia investigando la relación ambivalente y conflictiva entre la “arquitectura” y la “pintura.” La controversia en las formas y las técnicas de representación, que imponen sus ordenes sobre la naturaleza de la producción arquitectónica, se discute en relación con las fuerzas de las transformaciones tecnológicas accionadas por imperativos culturales más profundos. En la tradición occidental de la disciplina de la arquitectura, del siglo XV al siglo XX, ha existido una persistente división entre lo proyectual y lo pictórico. La división es todavía evidente en el momento de la propagación de la tecnología digital en la práctica de diseño desde los ochentas, cuando los gráficos vectoriales se hicieron cargo de la elaboración proyectual, y los gráficos en raster lidiaron con la manipulación pictórica. Sin embargo, hacia inicios del siglo XXI, una capacidad particular de inter-convertibilidad digital condujo a la disolución incidental de la división y al fin de la preponderancia de lo proyectual. La tecnología del renderizado hace que el proceso de visualizar retorne a la percepción de la “imagen de una sustancia.” Y, al mismo tiempo, la experimentación en forma animada dependiente de fuerzas, está supeditada a la habilidad para visualizar cálculos diferenciales rápidamente. En el final del texto se especula sobre las crecientes tendencias en la materialización pictórica y en la ingeniería de efectos como parte de un modelo diferente de producción arquitectónica, al que puede llamarse “introyectivo.