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RGB-D Videos Human Action Recognition: A Taxonomy-Based Survey to Learn the Discriminative Features 1

RGB-D Videos Human Action Recognition: A Taxonomy-Based Surv...

引用

1st International conference on Cognitive, Green and Ubiquitous Computing, IC-CGU 2024

作者： Padhan, Girish Electrical & Electronics Engineering Vikash Institute of Technology Biju patnaik University of Technology Odisha Bargarh India

ISBN: (纸本)9798350361780

In computer vision human action recognition plays an important role in the modern era. Here a sensor can acquired accurately the human action and their interactions from a previously unseen data sequence. Human activity identification in video sequences is a hotspot for computer vision research owing to its practical implications. It encompasses security, surveillance, healthcare, robotics, animation, sports analysis, smart home automation and behavioral analysis. The goal of AI society is to create a system that can observe and understand human behavior and actions completely independently. For example, a robot assistant might aid a patient undergoing home monitoring by analyzing the most effective method of exercise and so avoiding additional injuries, thereby increasing the robot's usefulness to society. This kind of smart technology will be immensely useful to us since it eliminates the need for unnecessary doctor visits, lowers healthcare costs, and allows for constant remote monitoring of the patient. Many feature-based methods, both manually designed and automatically taught, have emerged in the past two decades for identifying human actions in video footage. Traditional methods of human activity identification rely on meticulously designed characteristics that drill down to the most fundamental of motions. Over the last several years, deep learning algorithms have made great progress in a number of different domains, including human location prediction, object recognition, segmentation, audio analysis, object tracking, and super-resolution. In visual recognition tasks, the deep learning model is also crucial. Instead of manually extracting the characteristics, deep learning-based methods provide a more efficient and time-saving alternative. Handcrafted features solutions were shown to be effective, however they over-relied on feature descriptors when attempting action categorization. This type of problem needed additional man hours and specialized knowledge

关键词： computer vision

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Automatic colon segmentation using isolated-connected threshold

Automatic colon segmentation using isolated-connected thresh...

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1st International conference on robot, vision and Signal Processing, RVSP 2011

作者： Chang, Ku-Yaw Zhang, Hao-Han Chen, Shao-Jer Chen, Lih-Shyang Chen, Jia-Hong Department of Computer Science and Information Engineering Da-Yeh University Changhua Taiwan Department of Radiology Buddhist Dalin Tzu Chi General Hospital Chiayi Taiwan School of Medicine Buddhist Tzu Chi University Hualien Taiwan Department of Electrical Engineering National Cheng-Kung University Tainan Taiwan

ISBN: (纸本)9780769545813

Virtual colonoscopy (VC) is a safe and fast medical imaging procedure to screen the colon for polyps. And it has become very popular recently. Colon segmentation is a necessary and important step of such an examination procedure. In this paper, an automatic colon segmentation method is proposed. The fluid inside the colon is first identified and removed based on its characteristic of horizontal surface. A simple 3D region growing algorithm is applied to obtain initial segmentation of air, which is served as the basis of the ensuing automatic locating object and background seeds. Then the isolated-connected threshold algorithm, together with the above seeds, is applied to obtain the final results. The colon can be obtained by applying morphological operations to the segmentation results of air. Our proposed algorithm can automatically segment different substances based on the isolated-connected threshold. It allows the user to modify the segmentation results interactively by providing more object or background seeds. © 2011 IEEE.

关键词： Mathematical morphology

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An efficient scheme for monitoring sensory conditions in robot systems 1

An efficient scheme for monitoring sensory conditions in rob...

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1st IEEE International conference on robotics and Automation, ICRA 1984

作者： Chern, Ming-Yang Department of Electrical Engineering and Computer Science Korthwestern University EvanstonIL60201 United States

ISBN: (纸本)081860526X

An important use of sensing in robot systems is to initiate or terminate motions. The conditions for these actions are based on sensor data and thus called sensory conditions. The values of the sensor input may vary while the robot is moving or the environment is changing. Hence, the sensor data must be collected repetitively to support the updated evaluation of sensory conditions. In this paper, an efficient scheme for monitoring sensory conditions is presented. An auxiliary sensory processor is used to collect all sensor data (except the vision input) and monitor sensory conditions. Only the raw values of the sensor input will be checked to speed up the monitoring process. The threshold values of the raw data for matching sensory conditions are predetermined in the host computer and stored as a checking list in the sensory processor. The details of this scheme for different cases of sensory conditions are discussed. No floating point capability is needed for the sensory processor. © 1984 IEEE.

关键词： Digital arithmetic

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Design and FPGA-Implementation of 1^st-Order 4D IIR Frequency-Hyperplanar Digital Filters

Design and FPGA-Implementation of 1<SUP>st</SUP>-Order 4D II...

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54th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Madanayake, Arjuna Wimalagunaratne, Randeel Dansereau, Donald G. Bruton, Len T. Univ Akron Elect & Comp Engn Akron OH 44325 USA Univ Sydney Australian Ctr Field Robot Sch Aerosp Mech & Mech Engn Sydney NSW 2006 Australia Univ Calgary Elect & Comp Engn Calgary AB T2N 1N4 Canada

ISBN: (纸本)9781612848570

Four-dimensional (4D) 1(st)-order frequency-hyperplanar digital filters have emerging applications in computed tomography (CT), volumetric ultrasound, and light field processing for computer vision. A novel IIR architecture for real-time implementation of such filters is proposed, and two single-chip prototypes are implemented on Xilinx Virtex-4 Sx35ff668-10 FPGAs. Experimental results from the FPGA physical implementation as well as simulated 4D frequency responses of the two 4D IIR filter realizations are used to quantify the proposed circuits in terms of frequency response, speed and FPGA resource utilization.

关键词： CT FPGA implementation FPGA resource utilization IIR filters Xilinx Virtex-4 Sx35ff668-10 FPGA computed tomography computer vision field programmable gate arrays first-order 4D IIR frequency-hyperplanar digital filters four-dimensional IIR filter realizations frequency response light field processing real-time implementation simulated 4D frequency responses single-chip prototypes volumetric ultrasound

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Autonomous Underwater Vehicle for vision Based Tracking 1

Autonomous Underwater Vehicle for Vision Based Tracking

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

作者： Kumar, G. Santhan Painumgal, Unnikrishnan V. Kumar, M. N. V. Chaitanya Rajesh, K. H. V. Vignans Inst Informat Technol VSEZ Vadlapudi Post Visakhapatnam 530049 Andhra Pradesh India

This paper describes about the design, construction and control of an "Autonomous Underwater Vehicle for vision Based Tracking", built in Vignan's Institute of Information Technology, Centre for Innovation Lab. The underwater vision robot is essentially an Autonomous Underwater Vehicle (AUV) for study of marine animals by automatically tracking and following them using computer vision. The AUV can also be used as a platform for Photo-mapping of the Seafloor using the onboard camera and light arrangement. The robot is proposed to have 5 thrusters configurations to achieve 4 degrees of freedom controlled by an Inertial Measurement Unit (IMU) interfaced with control unit and powered by commercial LiPo battery packs. The robot is equipped with roll, pitch, heading, and depth sensors which provide sufficient feedback signals to automatically control the vehicle to track a pre-planned trajectory. The centre of gravity and centre of buoyancy of the vehicle are positioned in such a way that it is self-stabilized. Along with this the combinations of sensors and speed control drivers provide more stability to the system using a closed loop control system, without the operator involvement. The AUV also captures videos during its mission using the camera. It is planned to have a multi-core umbilical cable for video signal, water leakage alarm, feedback signals and battery charging lines. This will be only used for development and test purposes and will be removed during autonomous missions. Various control schemes can be applied for the vehicle to track different paths. The AUV is designed to the dimension of 575x210x175mm. The AUV uses O-rings for the hulls for good water sealing effect as well as for faster assembly and disassembly. We expect this AUV development to mature in to an advanced system can be used as a platform for study of the ocean by scientists, for environmental studies and for defense applications. (C) 2018 The Authors. Published by Elsevier Ltd.

关键词： Autonomous Underwater Vehicle vision Based Control System Image Tracking and Processing

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Synchronized video and motion capture dataset and quantitative evaluation of vision based skeleton tracking methods for robotic action imitation 1st

Synchronized video and motion capture dataset and quantitati...

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1st International conference on Information and Communication Technology for Development for Africa, ICT4DA 2017

作者： Atnafu, Selamawet Nicola, Conci Bahir Dar Institute of Technology Bahir Dar Ethiopia University of Trento Trento Italy

ISBN: (纸本)9783319951522

Marker-less skeleton tracking methods are being widely used for applications such as computer animation, human action recognition, human robot collaboration and humanoid robot motion control. Regarding robot motion control, using the humanoid’s 3D camera and a robust and accurate tracking algorithm, vision based tracking could be a wise solution. In this paper we quantitatively evaluate two vision based marker-less skeleton tracking algorithms (the first, Igalia’s Skeltrack skeleton tracking and the second, an adaptable and customizable method which combines color and depth information from the Kinect.) and perform comparative analysis on upper body tracking results. We have generated a common dataset of human motions by synchronizing an XSENS 3D Motion Capture System, which is used as a ground truth data and a video recording from a 3D sensor device. The dataset, could also be used to evaluate other full body skeleton tracking algorithms. In addition, sets of evaluation metrics are presented. © 2018, ICst Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Anthropomorphic robots

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Hierarchical Aggregation for 3D Instance Segmentation 18

Hierarchical Aggregation for 3D Instance Segmentation

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18th IEEE/CVF International conference on computer vision (ICCV)

作者： Chen, Shaoyu Fang, Jiemin Zhang, Qian Liu, Wenyu Wang, Xinggang Huazhong Univ Sci & Technol Sch EIC Wuhan Peoples R China Huazhong Univ Sci & Technol Inst AI Wuhan Peoples R China Horizon Robot Beijing Peoples R China

ISBN: (纸本)9781665428125

Instance segmentation on point clouds is a fundamental task in 3D scene perception. In this work, we propose a concise clustering-based framework named HAIS, which makes full use of spatial relation of points and point sets. Considering clustering-based methods may result in oversegmentation or under-segmentation, we introduce the hierarchical aggregation to progressively generate instance proposals, i.e., point aggregation for preliminarily clustering points to sets and set aggregation for generating complete instances from sets. Once the complete 3D instances are obtained, a sub-network of intra-instance prediction is adopted for noisy points filtering and mask quality scoring. HAIS is fast (only 410ms per frame on Titan X)) and does not require non-maximum suppression. It ranks 1st on the ScanNet v2 benchmark 1, achieving the highest 69:9% AP50 and surpassing previous state-of-the-art (SOTA) methods by a large margin. Besides, the SOTA results on the S3DIS dataset validate the good generalization ability. Code is available at https://***/hustvl/HAIS.

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Look Closer to Segment Better: Boundary Patch Refinement for Instance Segmentation

Look Closer to Segment Better: Boundary Patch Refinement for...

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IEEE/CVF conference on computer vision and Pattern Recognition (CVPR)

作者： Tang, Chufeng Chen, Hang Li, Xiao Li, Jianmin Zhang, Zhaoxiang Hu, Xiaolin Tsinghua Univ THU Bosch JCML Ctr State Key Lab Intelligent Technol & Syst Dept Comp Sci & TechnolInst AIBNRist Beijing Peoples R China Chinese Acad Sci Inst Automat Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Chinese Acad Sci Ctr Artificial Intelligence & Robot HKISI Beijing Peoples R China

ISBN: (纸本)9781665445092

Tremendous efforts have been made on instance segmentation but the mask quality is still not satisfactory. The boundaries of predicted instance masks are usually imprecise due to the low spatial resolution of feature maps and the imbalance problem caused by the extremely low proportion of boundary pixels. To address these issues, we propose a conceptually simple yet effective post-processing refinement framework to improve the boundary quality based on the results of any instance segmentation model, termed BPR. Following the idea of looking closer to segment boundaries better, we extract and refine a series of small boundary patches along the predicted instance boundaries. The refinement is accomplished by a boundary patch refinement network at higher resolution. The proposed BPR framework yields significant improvements over the Mask R-CNN baseline on Cityscapes benchmark, especially on the boundary-aware metrics. Moreover, by applying the BPR framework to the "PolyTransform + SegFix" baseline, we reached 1st place on the Cityscapes leaderboard. Code is available at https://***/tinyalpha/BPR.

关键词： Measurement computer vision Codes Benchmark testing Business process re-engineering Pattern recognition Spatial resolution

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A Novel Approach For Detection of Diabetic Macular Edema 1

A Novel Approach For Detection of Diabetic Macular Edema

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1st International conference on Emerging Trends in Engineering, Technology and Science (ICETETS)

作者： Johny, Anu Thomas, Abraham St Josephs Coll Engn & Technol Dept Elect & Commun Engn Palai Kerala India

ISBN: (纸本)9781467367257

Diabetic macular edema (DME) is an eye disease that belongs to diabetic retinopathy which directs to vision loss. DME, which is a contusion in the macular region of eye is a common vision problem seen in diabetic patients. Hard exudates (bright lesions) in the fundus image indicates the presence of DME. Early detection of Macular Edema in diabetic patients prevents blindness. DME occurs when fluid and protein deposits collect on or under the macula of the eye. These leakages cause the macula to thicken and swell, progressively distorts a persons vision. So in this article detection of exudates and its proximity towards macula determines and thereby its severity level. This article presents the computer based approach for the disease detection, which includes the steps image preprocessing, localization and masking of the optic disc, detection of fovea, ROI extraction, motion pattern generation, determination of disease severity level. First stage, detecting of DME and the next stage is assessing the severity of DME. An easier method for DME detection is also done.

关键词： Diabetic Macular Edema Fundus images Exudates ROI Rodon space

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A low-cost agriculture robot for dataset creation - Software and hardware solutions 1

A low-cost agriculture robot for dataset creation - Software...

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1st International conference on Innovative Engineering Sciences and Technological Research, ICIEstR 2024

作者： Kristian, Dokic Hrvoje, Kukina Hrvoje, Mikolcevic University of Osijek Faculty of Tourism and Rural Development Pozega Croatia Lira d.o.o. Lipik Development and Tourism Agency Lipik Croatia Technical School Pozega Croatia

ISBN: (数字)9798350348637

ISBN: (纸本)9798350348637

The limited availability of public image datasets continues to be a significant obstacle for the efficient development and assessment of computer vision and machine learning algorithms in agricultural production. This paper describes a simple robotic vehicle whose goal is to collect datasets, i.e. images of plants in the early stages of development. The vehicle is designed for vertical photography of root vegetables (carrots, beets, parsley, etc.) that do not have a large leaf mass. The goal of the development is to make the production of vehicles cheap and to speed up the creation of freely accessible datasets by making such or similar vehicles. The robotic vehicle uses cheap and easily available components, and ArUco markers are used for the navigation itself, which enables simple and precise navigation. © 2024 IEEE.

关键词： Vegetables

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