Image preprocessing for artistic robotic painting

Artistic robotic painting implies creating a picture on canvas according to a brushstroke map preliminarily computed from a source image. To make the painting look closer to the human artwork, the source image should be preprocessed to render the effects usually created by artists. In this paper, we consider three preprocessing effects: aerial perspective, gamut compression and brushstroke coherence. We propose an algorithm for aerial perspective amplification based on principles of light scattering using a depth map, an algorithm for gamut compression using nonlinear hue transformation and an algorithm for image gradient filtering for obtaining a well-coherent brushstroke map with a reduced number of brushstrokes, required for practical robotic painting. The described algorithms allow interactive image correction and make the final rendering look closer to a manually painted artwork. To illustrate our proposals, we render several test images on a computer and paint a monochromatic image on canvas with a painting robot

Aligning Figurative Paintings With Their Sources for Semantic Interpretation

This paper reports steps in probing the artistic methods of figurative painters through computational algorithms. We explore a comparative method that investigates the relation between the source of a painting, typically a photograph or an earlier painting, and the painting itself. A first crucial step in this process is to find the source and to crop, standardize and align it to the painting so that a comparison becomes possible. The next step is to apply different low-level algorithms to construct difference maps for color, edges, texture, brightness, etc. From this basis, various subsequent operations become possible to detect and compare features of the image, such as facial action units and the emotions they signify. This paper demonstrates a pipeline we have built and tested using paintings by a renowned contemporary painter Luc Tuymans. We focus in this paper particularly on the alignment process, on edge difference maps, and on the utility of the comparative method for bringing out the semantic significance of a painting

Video Manipulation Techniques for the Protection of Privacy in Remote Presence Systems

Systems that give control of a mobile robot to a remote user raise privacy concerns about what the remote user can see and do through the robot. We aim to preserve some of that privacy by manipulating the video data that the remote user sees. Through two user studies, we explore the effectiveness of different video manipulation techniques at providing different types of privacy. We simultaneously examine task performance in the presence of privacy protection. In the first study, participants were asked to watch a video captured by a robot exploring an office environment and to complete a series of observational tasks under differing video manipulation conditions. Our results show that using manipulations of the video stream can lead to fewer privacy violations for different privacy types. Through a second user study, it was demonstrated that these privacy-protecting techniques were effective without diminishing the task performance of the remote user.Comment: 14 pages, 8 figure

Robotic Arts: Painting a red canvas with a robotic arm

L'objectiu principal de l'art robòtic és crear art alhora que desenvolupar tècniques generals que es puguin utilitzar en altres contextos. En aquesta tesi es presenta un projecte dins l'àmbit de la Pintura Robòtica. Per tal d'iniciar el camí cap a un sistema robòtic de reproducció autònoma d'un quadre, l'objectiu d'aquesta tesi és aconseguir que un robot pinti uniformement un llenç de vermell. Per fer-ho, s'han d'utilitzar diferents tècniques, i el focus principal es posa en la planificació del moviment (motion planning). Presentem una tècnica general que resol el problema de resolució de redundància (redundancy resolution) donada una superfície d'espai de tasques restringit. Aquest és un enfocament basat en gràfics que s'utilitza per trobar un mínim del camí global segons criteris de cost integrals per la ruta. Es basa en un graf de Roadmap precalculat que representa la preimatge de la superfície de l'espai de tasques restringit. Amb aquest graf, es troba primer una solució a un problema aproximat, mitjançant una cerca feta per un graf de capes creat a partir del Roadmap original. Finalment, les solucions s'ajusten amb una optimització final mitjançant grafs factorials (Factor Graphs). Aquest mètode s'aplica amb èxit a la pintura robòtica. Les nombroses reconfiguracions possibles d'un robot entre pinzellades s'eviten mitjançant un ús intel·ligent del Roadmap. Gràcies a això, es mostra la flexibilitat i l'adaptabilitat que aquest mètode aporta en aquest context.El objetivo principal del arte robótico es crear arte a la vez que desarrollar técnicas generales que se puedan utilizar en otros contextos. En esta tesis se presenta un proyecto en el ámbito de la Pintura Robótica. Con el fin de iniciar el camino hacia un sistema robótico de reproducción autónoma de un cuadro, el objetivo de esta tesis es conseguir que un robot pinte uniformemente un lienzo de rojo. Para ello, deben utilizarse diferentes técnicas, cuyo foco principal se pone en la planificación del movimiento (motion planning). Presentamos una técnica general que resuelve el problema de resolución de redundancia (redundancy resolution) dada una superficie de espacio de tareas restringido. Éste es un enfoque basado en gráficos que se utiliza para encontrar un mínimo del camino global según criterios de coste integrales para la ruta. Se basa en un grafo de un Roadmap precalculado que representa la preimagen de la superficie del espacio de tareas restringido. Con este grafo, se encuentra primero una solución a un problema aproximado, mediante una búsqueda hecha en un grafo de capas creado a partir del Roadmap original. Por último, las soluciones se ajustan con una optimización final mediante grafos factoriales (Factor Graphs). Este método se aplica con éxito en la pintura robótica. Las numerosas reconfiguraciones posibles de un robot entre pinceladas se evitan mediante un uso inteligente del Roadmap. Gracias a ello, se muestra la flexibilidad y adaptabilidad que este método aporta en este contexto.The main goal in Robotic Arts is to create art while also developing general techniques that can be used in many other contexts. In this thesis, a project within the field of Robotic Painting is presented. In order to start the path to an autonomous painterly robotic reproduction system, the goal of this thesis is to get a robot to uniformly paint a canvas red. To do so, different techniques have to be used, and the main focus is put on the motion planning. We present a general technique that solves the redundancy resolution problem given a constrained task space surface. This is a graph-based approach used to find a global path minimum according to an integral path cost criteria. It is based on a precomputed Roadmap graph that represents the preimage of the constrained task space surface. With this graph, a solution to an approximate problem is found via a search on a Layered Graph representation of the previous original Roadmap. Finally, solutions are fine-tuned with an ending optimization via factor graphs. This method is then successfully applied to Robotic Painting. The many possible reconfigurations of a robot between strokes are evaded by a clever use of the Roadmap. Thanks to this, the flexibility and adaptability of this general method to this context is shown.Outgoin

Mobile Robotic Painting of Texture

Robotic painting is well-established in controlled factory environments, but there is now potential for mobile robots to do functional painting tasks around the everyday world. An obvious first target for such robots is painting a uniform single color. A step further is the painting of textured images. Texture involves a varying appearance, and requires that paint is delivered accurately onto the physical surface to produce the desired effect. Robotic painting of texture is relevant for architecture and in themed environments. A key challenge for robotic painting of texture is to take a desired image as input, and to generate the paint commands to as closely as possible create the desired appearance, according to the robotic capabilities. This paper describes a deep learning approach to take an input ink map of a desired texture, and infer robotic paint commands to produce that texture. We analyze the trade-offs between quality of reconstructed appearance and ease of execution. Our method is general for different kinds of robotic paint delivery systems, but the emphasis here is on spray painting. More generally, the framework can be viewed as an approach for solving a specific class of inverse imaging problems

Weak and Strong Computational Creativity

In the spirit of Searle’s definition of weak and strong artificial intelligence, this paper presents a discussion on weak computational creativity in swarm intelligence systems. It addresses the concepts of freedom and constraint and their impact on the creativity of the underlying systems. An analogy is drawn on mapping these two ‘prerequisites’ of creativity onto the two well-known phases of exploration and exploitation in swarm intelligence algorithms, followed by the visualisation of the behaviour of the swarms whose performance are evaluated in the context of arguments presented. The paper also discusses that the strong computational creativity is presented in ways emphasising that genuine creativity implies ‘genuine under- standing’ and other cognitive states, along with autonomy – asserting that without ‘Strong Embodiment’, computational systems are not genuinely autonomous