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1st International conference on Artificial Intelligence and Cognitive Computing, AICC 2018

1st International Conference on Artificial Intelligence and ...

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1st International conference on Artificial Intelligence and Cognitive Computing, AICC 2018

ISBN: (纸本)9789811315794

The proceedings contain 68 papers. The special focus in this conference is on Artificial Intelligence and Cognitive Computing. The topics include: Cognitive-based adaptive path planning for mobile robot in dynamic environment;prediction for indian road network images dataset using feature extraction method;Design and simulation of capacitive MEMS accelerometer;bioinformatics and image processing—Detection of plant diseases;hybrid approach for pixel-wise semantic segmentation using SegNet and squeezenet for embedded platforms;software modernization through model transformations;Semi-automatic annotation of images using eye gaze data (SAIGA);optimizing regression test suite reduction;application monitoring—Active learning approach;acquiring best rules that represent datasets;an automated computer vision system for extraction of retail food product metadata;attacks on two-key elliptic curve digital signature algorithm;bioinformatics: An application in information science;leveraging deep learning for anomaly detection in video surveillance;speaker diarization system using hidden Markov toolkit;Survey: Enhanced trust management for improving QoS in MANETs;a generic survey on medical big data analysis using internet of things;mean estimation under post-stratified cluster sampling scheme;privacy-preserving Naive Bayesian classifier for continuous data and discrete data;learning style recognition: A neural network approach;morphological-based localization of an Iris image;an enhanced efficiency of key management method for wireless sensor networks using mobile agents;a survey on emotion’s recognition using internet of things;KAZE feature based passive image forgery detection;efficiency-based analysis of homomorphic encryption implications;Performance and analysis of human attention using single-channel wireless EEG sensor for medical application;smart heartbeat monitoring system using machine learning.

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Color-based Object Categorization Model Using Fuzzy HSV Inference System 1

Color-based Object Categorization Model Using Fuzzy HSV Infe...

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1st International conference of Intelligent Computing and Engineering, ICOICE 2019

作者： Al-Hetar, Abdulaziz M Rassam, Murad A. Shormani, Osama Salem, Abdullah S. A. Al-Yousofi, Huthifa Communication and Computer Eng. Taiz University Taiz Yemen Qassim University Information Technology Dept. Buraidah Saudi Arabia Mechatronics Robotics Eng. Taiz University Taiz Yemen

ISBN: (纸本)9781728144870

Color is one of the most identifiable properties of objects and wide range of colors need to be detected. Images captured in RGB color space are hard to extract more than three colors from them due to their cubic shape of merging luminance, saturation, and color spectrum. This paper presents a color-based Object Categorization model that utilizes the HSV color space. The process starts by converting the RGB space into three main components, Hue (wavelength of colors), Saturation (purity of colors), and Value (grayness level or lightness), Unfortunately, Hue causes some sort of fogginess when color classification is applied, due to the gradient between each color. For that, the hue fuzzy sets are used which categorize colors in images. They are used to identify nine deferent object"s color and categorize them into the nine common pure colors. The categorization process is then carried out by a PUMA 560 robot in nine different trajectories based on the colors extracted by the fuzzy sets. In order to illuminate bright and dark objects and putting them into the tenth trajectory of the unwanted objects, we modified the saturation and value as fuzzy sets. The system is simulated, tested and proved its effectiveness in detecting colored objects due to their gradient and variations for environments with normal or highly structured light settings, using medium or high-resolution camera. © 2019 IEEE.

关键词： computer vision

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Fast event-driven incremental learning of hand symbols 1

Fast event-driven incremental learning of hand symbols

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1st IEEE International conference on Artificial Intelligence Circuits and Systems (AICAS)

作者： Lungu, Iulia-Alexandra Liu, Shih-Chii Delbruck, Tobi Univ Zurich Inst Neuroinformat Zurich Switzerland Swiss Fed Inst Technol Zurich Switzerland

ISBN: (纸本)9781538678848

This paper describes a hand symbol recognition system that can quickly be trained to incrementally learn to recognize new symbols using about 100 times less data and time than by using conventional training. It is driven by frames from a Dynamic vision Sensor (DVS) event camera. Conventional cameras have very redundant output, especially at high frame rates. Dynamic vision sensors output sparse and asynchronous brightness change events that occur when an object or the camera is moving. Images consisting of a fixed number of events from a DVS drive recognition and incremental learning of new hand symbols in the context of a RoShamBo (rock-paper-scissors) demonstration. Conventional training on the original RoShamBo dataset requires about 12.5h compute time on a desktop GPU using the 2.5 million images in the base dataset. Novel symbols that a user shows for a few tens of seconds to the system can be learned on-the-fly using the iCaRL incremental learning algorithm with 3 minutes of training time on a desktop GPU, while preserving recognition accuracy of previously trained symbols. Our system runs a residual network with 32 layers and maintains 88.4% after 100 epochs or 77% after 5 epochs overall accuracy after 4 incremental training stages. Each stage adds an additional 2 novel symbols to the base 4 symbols. The paper also reports an inexpensive robot hand used for live demonstrations of the base RoShamBo game.

关键词： neuromorphic event camera machine learning data-driven incremental learning robotics computer vision

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stAR-Net: Action recognition using spatiooral activation reprojection 16

STAR-Net: Action recognition using spatiooral activation rep...

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16th conference on computer and robot vision, CRV 2019

作者： McNally, William Wong, Alexander McPhee, John Dept. of Systems Design Engineering University of Waterloo WaterlooN2L 3G1 Canada

ISBN: (纸本)9781728118383

While depth cameras and inertial sensors have been frequently leveraged for human action recognition, these sensing modalities are impractical in many scenarios where cost or environmental constraints prohibit their use. As such, there has been recent interest on human action recognition using low-cost, readily-available RGB cameras via deep convolutional neural networks. However, many of the deep convolutional neural networks proposed for action recognition thus far have relied heavily on learning global appearance cues directly from imaging data, resulting in highly complex network architectures that are computationally expensive and difficult to train. Motivated to circumvent the challenges associated with training complex network architectures, we introduce the concept of spatiooral activation reprojection (stAR). More specifically, we reproject the spatiooral activations generated by human pose estimation layers in space and time using a stack of 3D convolutions. Experimental results on UTD-MHAD and J-HMDB demonstrate that an end-to-end architecture based on the proposed stAR framework (which we nickname stAR-Net) is proficient in single-environment and small-scale applications. On UTD-MHAD, stAR-Net outperforms several methods using richer data modalities such as depth and inertial sensors. © 2019 IEEE.

关键词： Convolution

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Military Surveillance robot Implementation Using robot Operating System 1

Military Surveillance Robot Implementation Using Robot Opera...

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1st International conference on Data Science and Analytics, PuneCon 2018

作者： Prakash, Aditya Walambe, Rahee Dept of Electronics and Telecommunication Symbiosis Institute of Technology Pune India

ISBN: (纸本)9781538672785

robots are becoming more and more prevalent in many real world scenarios. Housekeeping, medical aid, human assistance are a few common implementations of robots. Military and Security are also major areas where robotics is being researched and implemented. robots with the purpose of surveillance in war zones and terrorist scenarios need specific functionalities to perform their tasks with precision and efficiency. In this paper, we present a model of Military Surveillance robot developed using robot Operating System. The map generation based on Kinect sensor is presented and some test case scenarios are discussed with results. © 2018 IEEE.

关键词： computer vision

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RoboFI: Autonomous Path Follower robot for Human Body Detection and Geolocalization for Search and Rescue Missions using computer vision and IoT

RoboFI: Autonomous Path Follower Robot for Human Body Detect...

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International conference on Advances in Science, Engineering and robotics Technology

作者： Ahmed Imteaj M A Isfar Jubair Chowdhury Mohammad Farshid Abdur R Shahid School of Computing and Information Sciences Florida International University Department of Computer Science and Engineering International Islamic University

ISBN: (纸本)9781728134468

Numerous loss of lives is seen each year and the sum is consistently expanding because of destruction, fiasco, cataclysm and so forth these incorporate natural and man-made fiascoes. To counter this we have structured a rescue robot that is autonomous, it pursues track way by dint of 3 ultrasonic sensors in the front. For the processing work Raspberry Pi Model B is utilized which incorporates a grouping of single board processors. The smaller card size is handful as we are utilizing 4wd Car Chassis and a motor controller to drive it through. The robot features computer vision and raspberry pi camera module is used to help with the vision. We trained the camera utilizing algorithm to empower it identify movement, consequently after detecting movement the robot utilizes PIR to detect and affirm human presence. When human life is recognized in a destructed place the web application helps us to observe the live streaming of that found human and the closest environment. The coordination of GPS Module gives us a chance to see the area of where rescue activity is occurring. The web application that is designed by us likewise gives us a chance to do as such. After rescuing the detected individual, it goes on its merry way in repeating the flow of work that is assigned to it helping achieve maximum amount of success and lives saved. The reality to stun is, all these are incorporated in a solitary car chassis and the expense behind the work is insignificant. The reason is utilizing raspberry pi and our work to make a pi camera module ready to recognize movement by help of raspberry pi while incredible and expensive processors are required by and large.

关键词： Human detection Raspberry pi Autonomous robot Obstacle avoidance Raspberry pi camera module Live streaming Location Autonomous robots Obstacle avoidance images computer vision Perennial streams web applications Rescue Rescue robot robot Proportional integral Raspberries Collision avoidance Chance

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vision-based robot Manipulator for Industrial Applications 1

Vision-based Robot Manipulator for Industrial Applications

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1st International conference on robotics and Smart Manufacturing (RoSMa)

作者： Ali, Md. Hazrat Aizat, K. Yerkhan, K. Zhandos, T. Anuar, O. Nazarbayev Univ Sch Engn Astana 010000 Kazakhstan

This paper presents a multi-stage process of the development of a vision-based object sorting robot manipulator for industrial applications. The main aim of this research is to integrate vision system with the existing Scorbot in order to widen the capability of the integrated camera-robot system in industrial applications. Modern industrial robot Scorbot-ER 9 Pro is the focus of this research. Currently, the robot does not have an integrated vision system. Thus;a camera has been integrated to the robot gripper to achieve the target objectives. The main difficulties include establishing a relevant sequence of operations, developing a proper communication between camera and robot as well as the integration of the system components such as Matlab, Visual Basics, and Scorbase. (C) 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC -ND license (https://creativecommons orgilicense4by-tic-rd14 01) Peer-review under responsibility of the scientific committee of the International conference on robotics and Smart Manufacturing.

关键词： robot vision image processing programming

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An Autonomous Indoor Exploration robot Rover and 3D Modeling with Photogrammetry 1

An Autonomous Indoor Exploration Robot Rover and 3D Modeling...

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1st International ECTI-Northern-Section conference on Electrical, Electronics, computer and Telecommunications Engineering (ECTI-NCON)

作者： Graven, Olaf Hallan Srisuphab, Ananta Silapachote, Piyanuch Sirilertworakul, Variya Ampornwathanakun, Worrapol Anekwiroj, Pakawat Maitrichit, Nagorn Univ Coll Southeast Norway Dept Sci & Ind Syst Kongsberg Norway Mahidol Univ Fac Informat & Commun Technol Bangkok Thailand

ISBN: (纸本)9781538635520

An autonomous robot rover has been designed and developed. The proposed robot rover is capable of self-localization and self-exploration of a room or an area inside a building. Self-driving and self-navigating in unknown environments, our robot constantly scans its surrounding, incrementally and dynamically constructing a global map of the visited room. Immediately after it detects an obstacle or an obstruction, the robot car does not only stop or diverge its route in order to avoid crashing into it, but also marks its location on the map as dangerously hazard. All unoccupied spaces are registered as a safe path. While exploring, the robot is programmed to take a large number of photographs of its surrounding, which includes multiple views of each scene from multiple different angles. These images collected are used to create a three-dimensional model of the interior of the room by photogrammetric methods. In addition to a general exploration of desired regions, a robot may be presented with a selected target object. It must then chooses its own path to locate the object and to circle around it in order to take many photographs of it from all directions and to create a corresponding 3D model.

关键词： Autonomous automobiles Cameras Three-dimensional displays Laser radar Solid modeling robot vision systems

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Visual Search and Recognition for robot Task Execution and Monitoring 1

Visual Search and Recognition for Robot Task Execution and M...

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1st International conference on Applications of Intelligent Systems (APPIS)

作者： Mauro, Lorenzo Puja, Francesco Grazioso, Simone Ntouskos, Valsamis Sanzari, Marta Alati, Edoardo Freda, Luigi Pirri, Fiora Sapienza Univ Rome ALCOR Lab DIAG Rome Italy

ISBN: (纸本)9781614999294;9781614999287

Visual search of relevant targets in the environment is a crucial robot skill. We propose a preliminary framework for the execution monitor of a robot task, taking care of the robot attitude to visually searching the environment for targets involved in the task. Visual search is also relevant to recover from a failure. The framework exploits deep reinforcement learning to acquire a common sense scene structure and it takes advantage of a deep convolutional network to detect objects and relevant relations holding between them. The framework builds on these methods to introduce a vision-based execution monitoring, which uses classical planning as a backbone for task execution. Experiments show that with the proposed vision-based execution monitor the robot can complete simple tasks and can recover from failures in autonomy.

关键词： Artificial Intelligence computer vision and Pattern Recognition robotics

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Towards a Wearable Interface for Immersive Telepresence in robotics 5th

Towards a Wearable Interface for Immersive Telepresence in R...

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5th International conference on Arts and Technology, Interactivity and Game Creation (ArtsIT) / 1st International conference on Design, Learning and Innovation (DLI)

作者： Martinez-Hernandez, Uriel Szollosy, Michael Boorman, Luke W. Kerdegari, Hamideh Prescott, Tony J. Univ Leeds Inst Design Robot & Optimisat Leeds W Yorkshire England Univ Sheffield Sheffield Robot Lab Sheffield S Yorkshire England

ISBN: (纸本)9783319769080;9783319769073

In this paper we present an architecture for the study of telepresence, immersion and human-robot interaction. The architecture is built around a wearable interface that provides the human user with visual, audio and tactile feedback from a remote location. We have chosen to interface the system with the iCub humanoid robot, as it mimics many human sensory modalities, including vision (with gaze control) and tactile feedback, which offers a richly immersive experience for the human user. Our wearable interface allows human participants to observe and explore a remote location, while also being able to communicate verbally with others located in the remote environment. Our approach has been tested from a variety of distances, including university and business premises, and using wired, wireless and Internet based connections, using data compression to maintain the quality of the experience for the user. Initial testing has shown the wearable interface to be a robust system of immersive teleoperation, with a myriad of potential applications, particularly in social networking, gaming and entertainment.

关键词： Telepresence Immersion Wearable computing Human-robot interaction Virtual reality

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