Game designGame design is the process of creating and shaping the mechanics, systems, and rules of a game. Games can be created for entertainment, education, exercise, or experimental purposes. Increasingly, elements and principles of game design are also applied to other interactions, in the form of gamification.
Game art designGame art design is a subset of game development involving the process of creating the artistic aspects of video games. Video game art design begins in the pre-production phase of creating a video game. Video game artists are visual artists involved from the conception of the game who make rough sketches of the characters, setting, objects, etc. These starting concept designs can also be created by the game designers before the game is moved into actualization. Sometimes, these concept designs are called "programmer art".
Game design documentA game design document (often abbreviated GDD) is a highly descriptive living software design document of the design for a video game. A GDD is created and edited by the development team and it is primarily used in the video game industry to organize efforts within a development team. The document is created by the development team as result of collaboration between their designers, artists and programmers as a guiding vision which is used throughout the game development process.
Game balanceGame balance is a branch of game design with the intention of improving gameplay and user experience by balancing difficulty and fairness. Game balance consists of adjusting rewards, challenges, and/or elements of a game to create the intended player experience. Game balance is generally understood as introducing a level of fairness for the players. This includes adjusting difficulty, win-loss conditions, game states, economy balancing, and so on to work in tandem with each other. The concept of game balance depends on the game genre.
Digital image processingDigital image processing is the use of a digital computer to process s through an algorithm. As a subcategory or field of digital signal processing, digital image processing has many advantages over . It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and distortion during processing. Since images are defined over two dimensions (perhaps more) digital image processing may be modeled in the form of multidimensional systems.
Image segmentationIn and computer vision, image segmentation is the process of partitioning a into multiple image segments, also known as image regions or image objects (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics.
Linear–quadratic regulatorThe theory of optimal control is concerned with operating a dynamic system at minimum cost. The case where the system dynamics are described by a set of linear differential equations and the cost is described by a quadratic function is called the LQ problem. One of the main results in the theory is that the solution is provided by the linear–quadratic regulator (LQR), a feedback controller whose equations are given below. LQR controllers possess inherent robustness with guaranteed gain and phase margin, and they also are part of the solution to the LQG (linear–quadratic–Gaussian) problem.
Optimal controlOptimal control theory is a branch of mathematical optimization that deals with finding a control for a dynamical system over a period of time such that an objective function is optimized. It has numerous applications in science, engineering and operations research. For example, the dynamical system might be a spacecraft with controls corresponding to rocket thrusters, and the objective might be to reach the moon with minimum fuel expenditure.
Kalman filterFor statistics and control theory, Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe. The filter is named after Rudolf E. Kálmán, who was one of the primary developers of its theory.
