Download or read book Colour based Object Detection and Tracking for an Autonomous Quadrotor written by Hani Hunud Abia Kadouf and published by . This book was released on 2014 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Useful applications of Unmanned Air Vehicles (UAVs) include aerial surveillance in hostile military zones or search and rescue operations in disaster stricken areas. The increased visual capacity of UAVs also helps support ground vehicles during scouting missions or to extend communication beyond insurmountable land or water barriers. Computer vision techniques provide a simplistic means to convey information for motion control of a UAV. Hence this work focuses on the development of a vision based image processing algorithm for autonomous navigation of a quadrotor UAV. A camera was used to capture an aerial field of view and transmit a video stream of its perspective to a base station- where OpenCV 2.3.1 vision processing software was used to implement a vision processing algorithm. The algorithm comprises of colour thresholding, the use of image moment and blob detection to detect and track an object within the camea view. Experimental readings of an object's displacement at three altitudes; 1.5m, 2.0m and 2.5m were used to derive pixel-to-cm conversion equations based on the target's pixel coordinates on the viewing window. Through a statistical analysis of variance and standard deviation conducted on 15 experimental readings of displacement ranging from 5cm to 25cm; it was shown that the vision system is best suited for tracking displacements at lower altitude flights. Hence, the best result for variance and standard were achieved when using the derived equation and were 0.64 and 0.8 respectively. The equation derived was also used to derive GPS locking coordinates. Pixel coordinates of a target on the camera display were then used to produce GPS locking coordinates for the quadrotor to track a target object.
Download or read book OTA quadrotor written by Gavin Coelho and published by . This book was released on 2012 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Imaging Sensors and Technologies written by Gonzalo Pajares Martinsanz and published by MDPI. This book was released on 2018-07-06 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Imaging: Sensors and Technologies" that was published in Sensors
Download or read book Moving Object Detection and Segmentation for Remote Aerial Video Surveillance written by Teutsch, Michael and published by KIT Scientific Publishing. This book was released on 2015-03-11 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned Aerial Vehicles (UAVs) equipped with video cameras are a flexible support to ensure civil and military safety and security. In this thesis, a video processing chain is presented for moving object detection in aerial video surveillance. A Track-Before-Detect (TBD) algorithm is applied to detect motion that is independent of the camera motion. Novel robust and fast object detection and segmentation approaches improve the baseline TBD and outperform current state-of-the-art methods.
Download or read book 3D Object Detection and Tracking for Autonomous Vehicles written by Su Pang and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous driving systems require accurate 3D object detection and tracking to achieve reliable path planning and navigation. For object detection, there have been significant advances in neural networks for single-modality approaches. However, it has been surprisingly difficult to train networks to use multiple modalities in a way that demonstrates gain over single-modality networks. In this dissertation, we first propose three networks for Camera-LiDAR and Camera-Radar fusion. For Camera-LiDAR fusion, CLOCs (Camera-LiDAR Object Candidates fusion) and Fast-CLOCs are presented. CLOCs fusion provides a multi-modal fusion framework that significantly improves the performance of single-modality detectors. CLOCs operates on the combined output candidates before Non-Maximum Suppression (NMS) of any 2D and any 3D detector, and is trained to leverage their geometric and semantic consistencies to produce more accurate 3D detection results. Fast-CLOCs can run in near real-time with less computational requirements compared to CLOCs. Fast-CLOCs eliminates the separate heavy 2D detector, and instead uses a 3D detector-cued 2D image detector (3D-Q-2D) to reduce memory and computation. For Camera-Radar fusion, we propose TransCAR, a Transformer-based Camera-And-Radar fusion solution for 3D object detection. The cross-attention layer within the transformer decoder can adaptively learn the soft-association between the radar features and vision queries instead of hard-association based on sensor calibration only. Then, we propose to solve the 3D multiple object tracking (MOT) problem for autonomous driving applications using a random finite set-based (RFS) Multiple Measurement Models filter (RFS-M3). In particular, we propose multiple measurement models for a Poisson multi-Bernoulli mixture (PMBM) filter in support of different application scenarios. Our RFS-M3 filter can naturally model these uncertainties accurately and elegantly. We combine learning-based detections with our RFS-M3 tracker by incorporating the detection confidence score into the PMBM prediction and update step. We have evaluated our CLOCs, Fast-CLOCs and TransCAR fusion-based 3D detector and RFS-M3 3D tracker using challenging datasets including KITTI, nuScenes, Argoverse and Waymo that are released by academia and industry leaders. Superior experimental results demonstrated the effectiveness of the proposed approaches.
Download or read book UAV Sensors for Environmental Monitoring written by Felipe Gonzalez Toro and published by MDPI. This book was released on 2018-03-05 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "UAV Sensors for Environmental Monitoring" that was published in Sensors
Download or read book Color based Object Detection and Positioning written by Jian Cheng and published by . This book was released on 2003 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advanced Mechanical Science and Technology for the Industrial Revolution 4 0 written by Ligang Yao and published by Springer. This book was released on 2017-10-30 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes more than 30 papers from the first FZU-OPU-NTOU Joint Symposium on Advanced Mechanical Science and Technology for the Industrial Revolution 4.0, held at Fuzhou University, China, in December 2016. The symposium was organized by Fuzhou University (FZU), Osaka Prefecture University (OPU) and National Taiwan Ocean University (NTOU). The authors include several professors from universities in China, Japan, and Taiwan as well as four distinguished invited professors from Canada, Korea, Japan, and Taiwan. The book covers all important aspects related to the 4.0 industrial revolution: robotics and mechatronics; sensors, measurements, and instrumentation; mechanical dynamics and controls; mechanical design; vehicle systems and technologies; fluid mechanics; monitoring and diagnosis, prognosis, and health management; advanced signal processing; and big data; all of which are subjects with great potential in the field of mechanical engineering.
Download or read book Colour based Object Recognition written by J. Matas and published by . This book was released on 1995 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Autonomous Flying Robots written by Kenzo Nonami and published by Springer Science & Business Media. This book was released on 2010-09-15 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advance in robotics has boosted the application of autonomous vehicles to perform tedious and risky tasks or to be cost-effective substitutes for their - man counterparts. Based on their working environment, a rough classi cation of the autonomous vehicles would include unmanned aerial vehicles (UAVs), - manned ground vehicles (UGVs), autonomous underwater vehicles (AUVs), and autonomous surface vehicles (ASVs). UAVs, UGVs, AUVs, and ASVs are called UVs (unmanned vehicles) nowadays. In recent decades, the development of - manned autonomous vehicles have been of great interest, and different kinds of autonomous vehicles have been studied and developed all over the world. In part- ular, UAVs have many applications in emergency situations; humans often cannot come close to a dangerous natural disaster such as an earthquake, a ood, an active volcano, or a nuclear disaster. Since the development of the rst UAVs, research efforts have been focused on military applications. Recently, however, demand has arisen for UAVs such as aero-robotsand ying robotsthat can be used in emergency situations and in industrial applications. Among the wide variety of UAVs that have been developed, small-scale HUAVs (helicopter-based UAVs) have the ability to take off and land vertically as well as the ability to cruise in ight, but their most importantcapability is hovering. Hoveringat a point enables us to make more eff- tive observations of a target. Furthermore, small-scale HUAVs offer the advantages of low cost and easy operation.
Download or read book Geometrical and Contextual Scene Analysis for Object Detection and Tracking in Intelligent Vehicles written by Bihao Wang and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: For autonomous or semi-autonomous intelligent vehicles, perception constitutes the first fundamental task to be performed before decision and action/control. Through the analysis of video, Lidar and radar data, it provides a specific representation of the environment and of its state, by extracting key properties from sensor data with time integration of sensor information. Compared to other perception modalities such as GPS, inertial or range sensors (Lidar, radar, ultrasonic), the cameras offer the greatest amount of information. Thanks to their versatility, cameras allow intelligent systems to achieve both high-level contextual and low-level geometrical information about the observed scene, and this is at high speed and low cost. Furthermore, the passive sensing technology of cameras enables low energy consumption and facilitates small size system integration. The use of cameras is however, not trivial and poses a number of theoretical issues related to how this sensor perceives its environmen. In this thesis, we propose a vision-only system for moving object detection. Indeed,within natural and constrained environments observed by an intelligent vehicle, moving objects represent high risk collision obstacles, and have to be handled robustly. We approach the problem of detecting moving objects by first extracting the local contextusing a color-based road segmentation. After transforming the color image into illuminant invariant image, shadows as well as their negative influence on the detection process can be removed. Hence, according to the feature automatically selected onthe road, a region of interest (ROI), where the moving objects can appear with a high collision risk, is extracted. Within this area, the moving pixels are then identified usin ga plane+parallax approach. To this end, the potential moving and parallax pixels a redetected using a background subtraction method; then three different geometrical constraints : the epipolar constraint, the structural consistency constraint and the trifocaltensor are applied to such potential pixels to filter out parallax ones. Likelihood equations are also introduced to combine the constraints in a complementary and effectiveway. When stereo vision is available, the road segmentation and on-road obstacles detection can be refined by means of the disparity map with geometrical cues. Moreover, in this case, a robust tracking algorithm combining image and depth information has been proposed. If one of the two cameras fails, the system can therefore come back to a monocular operation mode, which is an important feature for perception system reliability and integrity. The different proposed algorithms have been tested on public images data set with anevaluation against state-of-the-art approaches and ground-truth data. The obtained results are promising and show that the proposed methods are effective and robust on the different traffic scenarios and can achieve reliable detections in ambiguous situations.
Download or read book Pattern Recognition written by Jesús Ariel Carrasco-Ochoa and published by Springer. This book was released on 2013-06-05 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th Mexican Conference on Pattern Recognition, MCPR 2013, held in Huatulco, Mexico, in June 2013. The 36 revised full papers and two keynotes presented were carefully reviewed and selected from 81 submissions and are organized in topical sections on computer vision; image processing; pattern recognition and artificial intelligence; neural networks; document processing.
Download or read book Computer Vision in Vehicle Technology written by Antonio M. López and published by John Wiley & Sons. This book was released on 2017-02-17 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified view of the use of computer vision technology for different types of vehicles Computer Vision in Vehicle Technology focuses on computer vision as on-board technology, bringing together fields of research where computer vision is progressively penetrating: the automotive sector, unmanned aerial and underwater vehicles. It also serves as a reference for researchers of current developments and challenges in areas of the application of computer vision, involving vehicles such as advanced driver assistance (pedestrian detection, lane departure warning, traffic sign recognition), autonomous driving and robot navigation (with visual simultaneous localization and mapping) or unmanned aerial vehicles (obstacle avoidance, landscape classification and mapping, fire risk assessment). The overall role of computer vision for the navigation of different vehicles, as well as technology to address on-board applications, is analysed. Key features: Presents the latest advances in the field of computer vision and vehicle technologies in a highly informative and understandable way, including the basic mathematics for each problem. Provides a comprehensive summary of the state of the art computer vision techniques in vehicles from the navigation and the addressable applications points of view. Offers a detailed description of the open challenges and business opportunities for the immediate future in the field of vision based vehicle technologies. This is essential reading for computer vision researchers, as well as engineers working in vehicle technologies, and students of computer vision.
Download or read book Handbook of Research on New Investigations in Artificial Life AI and Machine Learning written by Habib, Maki K. and published by IGI Global. This book was released on 2022-02-25 with total page 589 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology spreads globally, researchers and scientists continue to develop and study the strategy behind creating artificial life. This research field is ever expanding, and it is essential to stay current in the contemporary trends in artificial life, artificial intelligence, and machine learning. This an important topic for researchers and scientists in the field as well as industry leaders who may adapt this technology. The Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning provides concepts, theories, systems, technologies, and procedures that exhibit properties, phenomena, or abilities of any living system or human. This major reference work includes the most up-to-date research on techniques and technologies supporting AI and machine learning. Covering topics such as behavior classification, quality control, and smart medical devices, it serves as an essential resource for graduate students, academicians, stakeholders, practitioners, and researchers and scientists studying artificial life, cognition, AI, biological inspiration, machine learning, and more.
Download or read book Proceedings of 2021 International Conference on Autonomous Unmanned Systems ICAUS 2021 written by Meiping Wu and published by Springer Nature. This book was released on 2022-03-18 with total page 3575 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes original, peer-reviewed research papers from the ICAUS 2021, which offers a unique and interesting platform for scientists, engineers and practitioners throughout the world to present and share their most recent research and innovative ideas. The aim of the ICAUS 2021 is to stimulate researchers active in the areas pertinent to intelligent unmanned systems. The topics covered include but are not limited to Unmanned Aerial/Ground/Surface/Underwater Systems, Robotic, Autonomous Control/Navigation and Positioning/ Architecture, Energy and Task Planning and Effectiveness Evaluation Technologies, Artificial Intelligence Algorithm/Bionic Technology and Its Application in Unmanned Systems. The papers showcased here share the latest findings on Unmanned Systems, Robotics, Automation, Intelligent Systems, Control Systems, Integrated Networks, Modeling and Simulation. It makes the book a valuable asset for researchers, engineers, and university students alike.
Download or read book Information Science and Applications ICISA 2016 written by Kuinam J. Kim and published by Springer. This book was released on 2016-02-15 with total page 1439 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains selected papers from the 7th International Conference on Information Science and Applications (ICISA 2016) and provides a snapshot of the latest issues encountered in technical convergence and convergences of security technology. It explores how information science is core to most current research, industrial and commercial activities and consists of contributions covering topics including Ubiquitous Computing, Networks and Information Systems, Multimedia and Visualization, Middleware and Operating Systems, Security and Privacy, Data Mining and Artificial Intelligence, Software Engineering, and Web Technology. The contributions describe the most recent developments in information technology and ideas, applications and problems related to technology convergence, illustrated through case studies, and reviews converging existing security techniques. Through this volume, readers will gain an understanding of the current state-of-the-art information strategies and technologies of convergence security. The intended readers are researchers in academia, industry and other research institutes focusing on information science and technology.
Download or read book Sentiment Analysis and Deep Learning written by Subarna Shakya and published by Springer Nature. This book was released on 2023-01-01 with total page 987 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected papers presented at International Conference on Sentimental Analysis and Deep Learning (ICSADL 2022), jointly organized by Tribhuvan University, Nepal and Prince of Songkla University, Thailand during 16 – 17 June, 2022. The volume discusses state-of-the-art research works on incorporating artificial intelligence models like deep learning techniques for intelligent sentiment analysis applications. Emotions and sentiments are emerging as the most important human factors to understand the prominent user-generated semantics and perceptions from the humongous volume of user-generated data. In this scenario, sentiment analysis emerges as a significant breakthrough technology, which can automatically analyze the human emotions in the data-driven applications. Sentiment analysis gains the ability to sense the existing voluminous unstructured data and delivers a real-time analysis to efficiently automate the business processes.
