International Conference on Computer Vision Theory and Applications最新文献

Texture based image indexing and retrieval 基于纹理的图像索引和检索

International Conference on Computer Vision Theory and Applications Pub Date : 2018-09-20 DOI: 10.5220/0002065801770181

N. G. Rao, Dr. V Vijaya Kumar, V. V. Krishna

引用次数: 37

Application to Quantify Fetal Lung Branching on Rat Explants 定量大鼠外植体上胎儿肺分支的应用

International Conference on Computer Vision Theory and Applications Pub Date : 2018-09-02 DOI: 10.5220/0004220900670070

P. Rodrigues, S. Granja, António H. J. Moreira, N. Rodrigues, J. Vilaça

{"title":"Application to Quantify Fetal Lung Branching on Rat Explants","authors":"P. Rodrigues, S. Granja, António H. J. Moreira, N. Rodrigues, J. Vilaça","doi":"10.5220/0004220900670070","DOIUrl":"https://doi.org/10.5220/0004220900670070","url":null,"abstract":"Recently, regulating mechanisms of branching morphogenesis of fetal lung rat explants have been an essential tool for molecular research. The development of accurate and reliable segmentation techniques may be essential to improve research outcomes. This work presents an image processing method to measure the perimeter and area of lung branches on fetal rat explants. The algorithm starts by reducing the noise corrupting the image with a pre-processing stage. The outcome is input to a watershed operation that automatically segments the image into primitive regions. Then, an image pixel is selected within the lung explant epithelial, allowing a region growing between neighbouring watershed regions. This growing process is controlled by a statistical distribution of each region. When compared with manual segmentation, the results show the same tendency for lung development. High similarities were harder to obtain in the last two days of culture, due to the increased number of peripheral airway buds and complexity of lung architecture. However, using semiautomatic measurements, the standard deviation was lower and the results between independent researchers were more coherent.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129214993","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

Stereo vision for obstacle detection: A region-based approach 立体视觉障碍物检测:基于区域的方法

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-31 DOI: 10.5220/0002067900360045

P. Foggia, A. Limongiello, M. Vento

引用次数: 0

A Normalized Parametric Domain for the Analysis of the Left Ventricular Function 一种用于左心室功能分析的归一化参数域

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-31 DOI: 10.5220/0001074002670274

J. Garcia-Barnes, D. Gil, S. Pujadas, F. Carreras, M. Ballester

引用次数: 5

REFA3D: Robust Spatio-temporal Analysis of Video Sequences REFA3D:视频序列的鲁棒时空分析

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-31 DOI: 10.5220/0003857203520357

M. Grand-Brochier, C. Tilmant, M. Dhome

引用次数: 1

Advanced Player Activity Recognition by Integrating Body Posture and Motion Information 整合身体姿势和运动信息的高级玩家活动识别

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-30 DOI: 10.5220/0001754002610266

Marco Leo, T. D’orazio, P. Spagnolo, P. Mazzeo

引用次数: 1

Stereo Vision Head Vergence using GPU Cepstral Filtering 使用GPU倒谱滤波的立体视觉头部收敛

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-29 DOI: 10.5220/0003319406650670

Luís Almeida, P. Menezes, J. Dias

引用次数: 3

Real-time Gender Recognition for Uncontrolled Environment of Real-life Images 现实生活图像非受控环境下的实时性别识别

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-25 DOI: 10.5220/0002823203570362

Duan-Yu Chen, Kuan-Yi Lin

引用次数: 3

Robust Face Alignment Using Convolutional Neural Networks 基于卷积神经网络的鲁棒人脸对齐

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-23 DOI: 10.5220/0001073200300037

S. Duffner, Christophe Garcia

{"title":"Robust Face Alignment Using Convolutional Neural Networks","authors":"S. Duffner, Christophe Garcia","doi":"10.5220/0001073200300037","DOIUrl":"https://doi.org/10.5220/0001073200300037","url":null,"abstract":"Face recognition in real-world images mostly relies on three successive steps: face detection, alignment and identification. The second step of face alignment is crucial as the bounding boxes produced by robust face detection algorithms are still too imprecise for most face recognition techniques, i.e. they show slight variations in position, orientation and scale. We present a novel technique based on a specific neural architecture which, without localizing any facial feature points, precisely aligns face images extracted from bounding boxes coming from a face detector. The neural network processes face images cropped using misaligned bounding boxes and is trained to simultaneously produce several geometric parameters characterizing the global misalignment. After having been trained, the neural network is able to robustly and precisely correct translations of up to ±13% of the bounding box width, in-plane rotations of up to ±30◦ and variations in scale from 90% to 110%. Experimental results show that 94% of the face images of the BioID database and 80% of the images of a complex test set extracted from the internet are aligned with an error of less than 10% of the face bounding","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123916501","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: 13

Lightweight Computer Vision Methods for Traffic Flow Monitoring on Low Power Embedded Sensors 基于低功耗嵌入式传感器的交通流量监测轻量化计算机视觉方法

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-22 DOI: 10.5220/0005361006630670

M. Magrini, D. Moroni, G. Pieri, O. Salvetti

引用次数: 3