2019 Zooming Innovation in Consumer Technologies Conference (ZINC)最新文献

An Automated Procedure to Evaluate Usability of eHealth Platforms In The Wild 在野外评估电子健康平台可用性的自动化程序

2019 Zooming Innovation in Consumer Technologies Conference (ZINC) Pub Date : 2019-05-29 DOI: 10.1109/ZINC.2019.8769352

E. Ballarini, L. Ciabattoni, D. Domenichelli, M. Domenichelli, G. Foresi, A. Monteriù

引用次数: 1

Object detection and object tracking in front of the vehicle using front view camera 利用前视摄像头对车辆前方目标进行检测和跟踪

2019 Zooming Innovation in Consumer Technologies Conference (ZINC) Pub Date : 2019-05-29 DOI: 10.1109/ZINC.2019.8769367

Juraj Ciberlin, R. Grbić, N. Teslic, M. Pilipovic

{"title":"Object detection and object tracking in front of the vehicle using front view camera","authors":"Juraj Ciberlin, R. Grbić, N. Teslic, M. Pilipovic","doi":"10.1109/ZINC.2019.8769367","DOIUrl":"https://doi.org/10.1109/ZINC.2019.8769367","url":null,"abstract":"Modern vehicles are equipped with the different systems that help driver in the driving process ensuring safer and more comfortable driving. These systems are called Advanced Driver Assistance Systems (ADAS) and are step toward fully autonomous driving. The integral part of autonomous driving is an object detection and tracking by using front view camera which provides necessary information for emergency braking, collision avoidance, path planning, etc. In this paper, one possible approach to object detection and tracking in autonomous driving is presented. Two object detection methods are implemented and tested: Viola-Jones algorithm and YOLOv3. The Viola-Jones algorithm is used to create object detectors which detections are tracked in a video sequence. Nine object detectors were trained and they are divided into four groups (vehicle detectors, pedestrian detector, traffic light detector and traffic sign detectors). In second case, the YOLOv3 model was used for object detection. Both methods are evaluated in terms of accuracy and processing speed. For the purpose of object tracking, Median Flow tracking method and correlation tracking method are implemented and evaluated.","PeriodicalId":190326,"journal":{"name":"2019 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"437 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123418155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 16

Trajectory Planning for Autonomous Vehicle Using Digital Map 基于数字地图的自动驾驶汽车轨迹规划

2019 Zooming Innovation in Consumer Technologies Conference (ZINC) Pub Date : 2019-05-29 DOI: 10.1109/ZINC.2019.8769382

Jure Bajić, M. Herceg, Ivan Resetar, I. Velikic

引用次数: 1

Classification of Objects Detected by the Camera based on Convolutional Neural Network 基于卷积神经网络的摄像机检测目标分类

2019 Zooming Innovation in Consumer Technologies Conference (ZINC) Pub Date : 2019-05-29 DOI: 10.1109/ZINC.2019.8769392

Filip Kulić, R. Grbić, B. Todorović, Tihomir Anđelić

{"title":"Classification of Objects Detected by the Camera based on Convolutional Neural Network","authors":"Filip Kulić, R. Grbić, B. Todorović, Tihomir Anđelić","doi":"10.1109/ZINC.2019.8769392","DOIUrl":"https://doi.org/10.1109/ZINC.2019.8769392","url":null,"abstract":"Nowadays, we are trying to achieve as much vehicle autonomy as possible by developing Advanced Driver-Assistance Systems (ADAS). For such a system to make decisions, it should have insight into the environment of the vehicle, e.g. the objects surrounding the vehicle. During forward driving, the information about the objects in front of the vehicle is usually obtained by a front view in-vehicle camera. This paper describes the image classification method of the objects in the front of the vehicle based on deep convolutional neural networks (CNN). Such CNN is supposed to be implemented in embedded system of an autonomous vehicle and the inference should satisfy real-time constraints. This means that the CNN should be structured to have fast inference by reducing the number of operations as much as possible, but still having satisfying accuracy. This can be achieved by reducing the number of parameters which also means that the resulting network has lower memory requirements. This paper describes the process of realizing such a network, from image dataset development up to the CNN structuring and training. The proposed CNN is compared to the state-of-the-art deep neural network in terms of classification accuracy, inference speed and memory requirements.","PeriodicalId":190326,"journal":{"name":"2019 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122096934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automotive Vision Grabber: FPGA design, cameras and data transfer over PCIe 汽车视觉捕捉器:FPGA设计，摄像头和PCIe数据传输

2019 Zooming Innovation in Consumer Technologies Conference (ZINC) Pub Date : 2019-05-29 DOI: 10.1109/ZINC.2019.8769348

I. Vidó, Ivana Škorić, Dominik Mitrović, M. Milosevic, M. Herceg

引用次数: 5

Software solution stack for data transfer on a frame grabber platform 帧采集平台上数据传输的软件解决方案栈

2019 Zooming Innovation in Consumer Technologies Conference (ZINC) Pub Date : 2019-05-29 DOI: 10.1109/ZINC.2019.8769412

Ivan Benke, Bože Eugen Marković, Ivan Pavlović, M. Milosevic, R. Grbić

{"title":"Software solution stack for data transfer on a frame grabber platform","authors":"Ivan Benke, Bože Eugen Marković, Ivan Pavlović, M. Milosevic, R. Grbić","doi":"10.1109/ZINC.2019.8769412","DOIUrl":"https://doi.org/10.1109/ZINC.2019.8769412","url":null,"abstract":"With the progress of automotive industry arose a need for development of fully autonomous vehicles. Such vehicle is equipped with sensors and cameras designed for monitoring its surroundings. Data received from these sensors is then processed in the vehicle’s embedded system which contains algorithms that help driver in a driving process and are a step towards a fully autonomous vehicle. Due to the problem complexity, these algorithms are usually based on machine learning methods and thus inherently require large amounts of data for successful training. Data used for training is mostly video content of situations from actual traffic. To record that video content specialized hardware and its accompanying software is needed. This paper focuses on developing software for existing AMV Grabber hardware board. Entire software stack was developed, from low-level application which controls the hardware directly, through device driver which enables communication between the board and PC, to PC application which enables users to control the hardware indirectly, i.e., to send commands to the board to start or stop recording. PC application is also used to receive data from the board and store it on non-volatile memory of the PC. Finally, measurements were done to display overall system performance.","PeriodicalId":190326,"journal":{"name":"2019 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"03 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114231820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Design and development of a smart attendance management system with Bluetooth low energy beacons 基于蓝牙低功耗信标的智能考勤管理系统的设计与开发

2019 Zooming Innovation in Consumer Technologies Conference (ZINC) Pub Date : 2019-05-29 DOI: 10.1109/ZINC.2019.8769433

Bruno Zoric, Mario Dudjak, Drazen Bajer, G. Martinović

{"title":"Design and development of a smart attendance management system with Bluetooth low energy beacons","authors":"Bruno Zoric, Mario Dudjak, Drazen Bajer, G. Martinović","doi":"10.1109/ZINC.2019.8769433","DOIUrl":"https://doi.org/10.1109/ZINC.2019.8769433","url":null,"abstract":"Tracking of attendance is a ubiquitous task in many institutions and during organised events. This, along with subsequent management of collected data can be a cumbersome activity that requires significant time and effort, from all involved parties. Tracking and managing student attendance during lectures and exams is an especially important instance of that task. Automated attendance management systems devised in the literature differ in applied technological solutions and features. However, many of these lack some features that would make them particularly useful for the task of student attendance management. This paper proposes the design of an automatic system tailored for the tracking and management of student attendance data. The design incorporates three main components that interact to deliver a seamless user experience. The key element is the utilisation of simple beacons, which make the system cost-effective and easy to use. Combining them with a mobile platform and a web service enables versatile attendance tracking. Periodic detection of the nearby beacons with authenticated server-side logic makes the proposed design unique in terms of addressing common attendance tracking issues. Also, the design is open for future integration of sophisticated data analysis modules.","PeriodicalId":190326,"journal":{"name":"2019 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122240835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Field Trial Results for Portable Indoor Reception of the DVB-T2 Base Profile 便携式室内接收DVB-T2基本轮廓的实地试验结果

2019 Zooming Innovation in Consumer Technologies Conference (ZINC) Pub Date : 2019-05-01 DOI: 10.1109/ZINC.2019.8769387

Ioan Tache

引用次数: 1

Educational microprocessor implementation on ZYNQ reconfigurable system on chip 基于ZYNQ可重构系统的教育微处理器片上实现

2019 Zooming Innovation in Consumer Technologies Conference (ZINC) Pub Date : 2019-05-01 DOI: 10.1109/ZINC.2019.8769381

Balaz Petrovic, I. Mezei

引用次数: 2

Employee wellbeing in the digital age 数字时代的员工幸福感

2019 Zooming Innovation in Consumer Technologies Conference (ZINC) Pub Date : 2019-05-01 DOI: 10.1109/ZINC.2019.8769391

Milica Vukelić, Svetlana Cizmic

引用次数: 3