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Committee Members of the Conference

Programme Chair

Prof. (Dr.) Srikanta Patnaik Chairman, I.I.M.T., Bhubaneswar Intersceince Campus, At/Po.: Kantabada, Via-Janla, Dist-Khurda Bhubaneswar, Pin:752054. Orissa, INDIA.

About the Conference

With an emerging and exponential growth of computational solutions to multifarious sociotechnical problems, the field of computer science is celebrated with radical innovations and advancements. The standing philosophy of such an enduring discipline is to duplicate the abilities of human vision by electronically perceiving and understanding an image. This image understanding can be seen as the disentangling of symbolic information from image data using models constructed with the aid of geometry, physics, statistics, and learning theory. As a technological discipline, computer vision seeks to apply its theories and models to the construction of computer vision systems. Examples of applications of computer vision include systems for, Controlling processes (e.g., an industrial robot), navigation (e.g. by an autonomous vehicle or mobile robot), detecting events (e.g., for visual surveillance or people counting), organizing information (e.g., for indexing databases of images and image sequences), modeling objects or environments (e.g., medical image analysis or topographical modeling), interaction (e.g., as the input to a device for computer-human interaction), automatic inspection, e.g. in manufacturing applications. The field is embodied with diversified with many application areas such as: medical computer vision or medical image processing. This area is characterized by the extraction of information from image data for the purpose of making a medical diagnosis of a patient. Generally, image data is in the form of microscopy images, X-ray images, angiography images, ultrasonic images, and tomography images. A second application area in computer vision is in industry, sometimes called machine vision, where information is extracted for the purpose of supporting a manufacturing process. Military applications are probably one of the largest areas for computer vision. The obvious examples are detection of enemy soldiers or vehicles and missile guidance. One of the newer application areas is autonomous vehicles, which include submersibles, land-based vehicles (small robots with wheels, cars or trucks), aerial vehicles, and unmanned aerial vehicles (UAV). The organization of a computer vision system is highly application dependent. Some systems are stand-alone applications which solve a specific measurement or detection problem, while others constitute a sub-system of a larger design which, for example, also contains sub-systems for control of mechanical actuators, planning, information databases, man-machine interfaces, etc. The specific implementation of a computer vision system also depends on if its functionality is pre-specified or if some part of it can be learned or modified during operation. The concept and creation of machines that could operate autonomously dates back to classical times, but research into the functionality and potential uses of robots did not grow substantially until the 20th century. Today, robotics is a rapidly growing field, as we continue to research, design, and build new robots that serve various practical purposes, whether domestically, commercially, or militarily. Many robots do jobs that are hazardous to people such as defusing bombs, exploring shipwrecks, and mines.


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robotics, locomotion, arm, charging, memory.


Computational Engineering | Computer Engineering | Robotics


The field of Robotics has surpassed a long journey since third century before Christ by Yan Shi and still it continues. The mechanical structure of a robot must be controlled to perform tasks. The control of a robot involves three distinct phases - perception, processing, and action (robotic paradigms). Sensors give information about the environment or the robot itself (e.g. the position of its joints or its end effector). This information is then processed to calculate the appropriate signals to the actuators (motors) which move the mechanical. A first particular new innovation in robot design is the open sourcing of robot-projects. To describe the level of advancement of a robot, the term "Generation Robots" can be used. This term is coined by Professor Hans Moravec, Principal Research Scientist at the Carnegie Mellon University Robotics Institute in describing the near future evolution of robot technology. First generation robots, Moravec predicted in 1997, should have an intellectual capacity comparable to perhaps a lizard and should become available by 2010. Because the first generation robot would be incapable of learning, however, Moravec predicts that the second generation robot would be an improvement over the first and become available by 2020, with the intelligence maybe comparable to that of a mouse. The third generation robot should have the intelligence comparable to that of a monkey. Though fourth generation robots, robots with human intelligence, professor Moravec predicts, would become possible, he does not predict this happening before around 2040 or 2050. The second is Evolutionary Robots. This is a methodology that uses evolutionary computation to help design robots, especially the body form, or motion and behavior controllers. In a similar way to natural evolution, a large population of robots is allowed to compete in some way, or their ability to perform a task is measured using a fitness function. Those that perform worst are removed from the population, and replaced by a new set, which have new behaviors based on those of the winners. Over time the population improves, and eventually a satisfactory robot may appear. This happens without any direct programming of the robots by the researchers. Researchers use this method both to create better robots, and to explore the nature of evolution. Because the process often requires many generations of robots to be simulated, this technique may be run entirely or mostly in simulation, then tested on real robots once the evolved algorithms are good enough. Currently, there are about 1 million industrial robots toiling around the world, and Japan is the top country having high density of utilizing robots in its manufacturing industry. As the area is broad and requires cross functionally expert reviewers for technical scrutiny of the papers, we have tried to impart justice to all the paper in its publication in the proceeding. In all sense we have been transcendental in this field in developing the fauna of the conference. In meeting the professional commitments we maintained the sanctity by adhering to ethics, ontology and semiotics. I beg apology for any inconveniency caused to the participants and delegates in the journey of this conference. I have regards for the IRNet family members, reviewers, and support staffs for their generous gifts of time, energy and effort. Specifically I owe indebtedness to the authors for their intellectual contributions in this conference. The conference is designed to stimulate the young minds including Research Scholars, Academicians, and Practitioners to contribute their ideas, thoughts and nobility in these two integrated disciplines. I must acknowledge your response to this conference. I ought to convey that this conference is only a little step towards knowledge, network and relationship I express best wishes to all the paper presenters. I extend my heart full thanks to the reviewers, editorial board members, programme committee members of the conference. If situations prevail in favor we will take the glory of organizing the second conference of this kind during this period next year. Editor-in-Chief Prof. Srikanta Patnaik, Professor, Computer Science and Engineering, ITER, SOA University, Bhubaneswar Dist. Khurda 752 024, Orissa, INDIA

Proceedings of International Conference on Computational Vision & Robotics