Self-adjusting focus of attention in combination with a genetic fuzzy system for improving a laser environment control device system
Graphical abstract
Section snippets
Introducction
Human beings feature both the desire and need to control the environment, probably as a result of attempting to improve their quality of life. For example, in prehistory when fire taming could mean a difference between life and death; later on history while managing and manipulating natural resources as in agriculture; and more recently with the arrival of the technological society where a plethora of electronic devices are nowadays part of our life.
Today, every conventional-home features tens
Releated works
In the literature, different environment control systems have already been described; see [4], [6], [16], [17], [18], [19], [20], [21], [22]. Note that, a large set of previous works, where different techniques are used, are based on laser pointers; see Table 1. In those works, the goal is to interact with a projection screen by means of the laser pointer. In our previous works, we attempt to extend similar capabilities in such a way of enhancing the interaction with devices considering a
Classical vision techniques
We describe here some of the classic computer vision techniques we have employed as our base case for comparison. As described above these techniques have been frequently employed before, (see Table 1), and allows us to compare their behaviours. Moreover, we already considered such techniques in some of our previous works [5], [6], [7], [8], [9], [10], [11], [12].
System description
In order to provide with a home environment laser-pointer interactive system, we need a number of modules that cooperate to achieve the desired functionality. Although the main goal of this paper is to improve the laser-spot detection system, we provide here a summary of the whole system including their components and relationships. In particular, the system includes a tool that helps the system to adapt to new environments by providing the location of controllable devices. We consider that the
Focus of attention and its application for the improvement of a laser-spot detection system
Although other approaches were followed to improve the results achieved by the described techniques; see [6], [7], [8], [9], [10], [11], [12], TM was always the base for the feature extraction process. It was noteworthy that every time that a new method was proposed an improvement was attained; nevertheless, we remark that TM was the main source of false negatives that persistently deteriorated the results. Hence, this algorithm tends to find, under certain conditions, images sections that do
FOA experimental design
Before presenting the results, we must consider that FOA uses a GP based algorithm as a self-adjusting process. It is therefore necessary to provide a large set of examples to achieve a correct training process while obtaining the best results. The set consists of 480 images, selected from 990 images acquired with a real system operating in a home environment. The images used by the self-adjusting process are only those containing the laser spot. Thus, the applied images have the following
Conclusions
This paper shows the interest of a self-adjusting the GP-based focus of attention technique when working in collaboration with classical computer vision techniques and genetic fuzzy systems for a specific problem: the accurate detection of laser spots. The main goal is to offer a reliable user interface with standard domotic systems based on laser pointers and video cameras, which are capable of detecting user actions and sending the appropriate orders to devices.
Previous works showed us that
Acknowledgements
This work has been supported by the Seventh Framework Programme of the European Union through the Marie Curie International Research Staff Scheme, FP7-PEOPLE-2013-IRSES, Grant 612689 ACoBSEC, Spanish Ministry of Science and Innovation under project TIN2011-28627-C04-03, regional government “Gobierno de Extremadura, Consejería de Economía-Comercio e Innovación” and FEDER, project GRU10029. This work is also sponsored by CONACyT México through the project 155045 – “Evolución de Cerebros
References (76)
- et al.
A review of smart homes – present state and future challenges
Comput. Methods Programs Biomed.
(2008) - et al.
Ten years of genetic fuzzy systems: current framework and new trends
Fuzzy Sets Syst.
(2004) - et al.
Non-invasive brain–computer interface system: towards its application as assistive technology
Brain Res. Bull.
(2008) - et al.
Lumipoint: multi-user laser-based interaction on large tiled displays
Displays
(2002) - et al.
Laser spot location method for a laser pointer interaction application using a diffractive optical element
Opt. Laser Technol.
(2007) - et al.
A feature-integration theory of attention
Cogn. Psychol.
(1980) - et al.
Modeling attention to salient proto-objects
Neural Netw.
(2006) Fuzzy sets
Inf. Control
(1965)Is there a need for fuzzy logic?
Inf. Sci.
(2008)- et al.
Tuning fuzzy logic controllers by genetic algorithms
Int. J. Approx. Reason.
(1995)
Integrated fuzzy logic and genetic algorithmic approach for simultaneous localization and mapping of mobile robots
Appl. Soft Comput.
A genetic learning process for the scaling factors, granularity and contexts of the fuzzy rule-based system data base
Inf. Sci.
LARES: an intelligent sweet home for assisting the elderly and the handicapped
User-friendly interaction/interface control of intelligent home for movement-disabled people
Understanding the dynamics of technological configurations: a conceptual framework and the case of smart homes
Technol. Forecast. Soc. Change
Self-adjusting focus of attention by means of GP for improving a laser point detection system
An independent and non-intrusive laser pointer environment control device system
Hybrid laser pointer detection algorithm based on template matching and fuzzy rule-based systems for domotic control in real home environments
Appl. Intell.
Environment control for handicapped people by laser pointer and template matching (Spanish)
Evolutionary tuned of a fuzzy rule-based system for a system control environment by means of a laser pointer (Spanish)
Evolutionary learning of a laser pointer detection fuzzy system for an environment control system
Genetic tuning of a laser pointer environment control device system for handicapped people with fuzzy systems
Automatic laser pointer detection algorithm for environment control device systems based on template matching and genetic tuning of fuzzy rule-based systems
Int. J. Comput. Intell. Syst.
Genetic fuzzy systems: taxonomy, current research trends and prospects
Evol. Intell.
A review of smart homes past, present, and future
IEEE Trans. Syst. Man Cybern. C: Appl. Rev.
Smart home research
Personalization and multi-user management in smart homes for disabled people
Int. J. Smart Home
The design of smart homes for people with dementia user-interface aspects
Univers. Access Inf. Soc.
Intelligent systems and smart homes
Inf. Syst. Front.
Robotic smart house to assist people with movement disabilities
Auton. Robot.
A point-and-click interface for the real world: laser designation of objects for mobile manipulation
Interaction with a projection screen using a camera-tracked laser pointer
Laser pointer interaction
Development of position recording system on structural surface using laser pointer
Laser spot detection
J. Inf. Control Manage. Syst.
Recognition of character drawn on screen with laser pointer
Vision based laser pointer interaction for flexible screens
Cited by (10)
Observer-based method for synchronization of uncertain fractional order chaotic systems by the use of a general type-2 fuzzy system
2016, Applied Soft Computing JournalCitation Excerpt :In [23] fuzzy and ant colony optimization based method is presented for wireless sensor networks. The genetic and particle swarm optimization algorithms are used in [24,25], to optimize type-1 fuzzy based controllers. A review of the bio-inspired methods used in the interval type-2 fuzzy controllers is considered in [20].
Automated Design of Salient Object Detection Algorithms with Brain Programming
2022, Applied Sciences (Switzerland)Time and Individual Duration in Genetic Programming
2020, IEEE AccessArtificial Visual Cortex and Random Search for Object Categorization
2019, IEEE AccessCUDA-based parallelization of a bio-inspired model for fast object classification
2018, Neural Computing and Applications