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2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)最新文献

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Pedestrian positioning in urban city with the aid of Google maps street view 借助谷歌地图街景的城市行人定位
2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) Pub Date : 2017-05-01 DOI: 10.23919/MVA.2017.7986899
Haitao Wang, Yanlei Gu, S. Kamijo
{"title":"Pedestrian positioning in urban city with the aid of Google maps street view","authors":"Haitao Wang, Yanlei Gu, S. Kamijo","doi":"10.23919/MVA.2017.7986899","DOIUrl":"https://doi.org/10.23919/MVA.2017.7986899","url":null,"abstract":"Pedestrian navigation has become one of the most used services in people's city lives. Not only smartphone based navigation, but also the application in the next generation of intelligent wearable devices, such as smart glasses, attract attentions from both scientists and engineers. The satisfied navigation service requires an accurate positioning technology. Even though the current smartphones have integrated various sensors, such as Global Navigation Satellite System receiver, gyroscope, accelerometer and magnetometer sensors, the performance of positioning in city urban is still not satisfied. The reasons of the errors include GNSS signals reflections, high dynamic of pedestrian activities and disturbance of the magnetic field in city environments. This paper proposes to utilize the camera sensor for improving the accuracy of the positioning. The camera sensor provides the visual observation for surround environment. This observation is compared with the available Google Maps Street View in order to correct positioning errors. With the visual matching between the geo-tagged pedestrian's photo and the reference images from Google Maps Street View, we expect to reduce the positioning error into 4 meters, and further recognize which side of the road or which corner of the crossroads the pedestrian is in.","PeriodicalId":193716,"journal":{"name":"2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117348333","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: 4
A study of virtual visual servoing sensitivity in the context of image/GIS registration for urban environments 城市环境图像/GIS配准下的虚拟视觉伺服灵敏度研究
2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) Pub Date : 2017-05-01 DOI: 10.23919/MVA.2017.7986915
Hengyang Wei, M. Pressigout, L. Morin, M. Servieres, G. Moreau
{"title":"A study of virtual visual servoing sensitivity in the context of image/GIS registration for urban environments","authors":"Hengyang Wei, M. Pressigout, L. Morin, M. Servieres, G. Moreau","doi":"10.23919/MVA.2017.7986915","DOIUrl":"https://doi.org/10.23919/MVA.2017.7986915","url":null,"abstract":"This paper studies the sensitivity of pose estimation to the 2D measure noise when using virtual visual servoing. Attempting to apply virtual visual servoing to image/Geographic Information System (GIS) registration, the robustness to the noise in images is an important factor to the accuracy of estimation. To analyze the impact of different levels of noise, a series of image/GIS registration tests based on synthetic input image are studied. Also, RANSAC is introduced to improve the robustness of the method. We also compare some different strategies in choosing geometrical features and in the treatment of projection error vector in virtual visual servoing, providing a guide for parametrization.","PeriodicalId":193716,"journal":{"name":"2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127862055","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: 1
Fast, versatile, and non-destructive biscuit inspection system using spectral imaging 快速，通用，无损饼干检测系统使用光谱成像
2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) Pub Date : 2017-05-01 DOI: 10.23919/MVA.2017.7986910
J. Carstensen
{"title":"Fast, versatile, and non-destructive biscuit inspection system using spectral imaging","authors":"J. Carstensen","doi":"10.23919/MVA.2017.7986910","DOIUrl":"https://doi.org/10.23919/MVA.2017.7986910","url":null,"abstract":"A fast, versatile, and non-destructive method for assessing biscuit quality is presented. The method integrates color (or browning) measurement, moisture assessment, compositional and dimensional measurements on a spectral imaging platform using the silicon range 400–1000 nm.","PeriodicalId":193716,"journal":{"name":"2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127918564","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
Detection of self intersection in synthetic hand pose generators 合成手姿生成器的自交检测
2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) Pub Date : 2017-05-01 DOI: 10.23919/MVA.2017.7986874
Shome S. Das
{"title":"Detection of self intersection in synthetic hand pose generators","authors":"Shome S. Das","doi":"10.23919/MVA.2017.7986874","DOIUrl":"https://doi.org/10.23919/MVA.2017.7986874","url":null,"abstract":"Synthetic hand pose data has been frequently used in vision based hand gesture recognition. However existing synthetic hand pose generators are not able to detect intersection between various hand parts and can synthesize self intersecting poses. Using such data may lead to learning wrong models. We propose a method to eliminate self intersecting synthetic hand poses by accurately detecting intersections between various hand parts. We model each hand part as a convex hull and calculate pairwise distance between the parts, labeling any pair with a negative distance as intersecting. A hand pose with at least one pair of intersecting parts is labeled as self intersecting. We show experimentally that our method is very accurate and performs better than existing techniques. We also show that it is fast enough for offline data generation.","PeriodicalId":193716,"journal":{"name":"2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131027825","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: 1
A neural network approach to visual tracking 视觉跟踪的神经网络方法
2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) Pub Date : 2017-05-01 DOI: 10.23919/MVA.2017.7986881
Zhe Zhang, K. Wong, Zhiliang Zeng, Lei Zhu
{"title":"A neural network approach to visual tracking","authors":"Zhe Zhang, K. Wong, Zhiliang Zeng, Lei Zhu","doi":"10.23919/MVA.2017.7986881","DOIUrl":"https://doi.org/10.23919/MVA.2017.7986881","url":null,"abstract":"Fully Convolution Networks (FCNs) have been shown to be effective in semantic segmentation through fine-tuning classification networks on segmentation data. In this paper, we present that FCNs can be further fine-tuned on target-background images in order to solve visual tracking problems. Pixel level models (FCNs) trained on segmentation data are superior to class level models (e.g. VGG net and GoogLeNet) in visual tracking tasks due to their powerful ability in discriminating between objects and background. Our work is based on a FCN network structure. The result is achieved by first fine-tuning the first image of a sequence and then the tracking and updating processes are conducted through classical forward and backward processes of neural networks. The proposed model achieves high precision and tracking success rates in online object tracking benchmark (OTB) data. It indicates our approach is competitive to state-of-the-art approaches as well.","PeriodicalId":193716,"journal":{"name":"2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132045895","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
Estimation of radial distortion using local spectra of planar textures 利用平面纹理局部谱估计径向畸变
2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) Pub Date : 2017-05-01 DOI: 10.23919/MVA.2017.7986903
Benjamin Spitschan, J. Ostermann
{"title":"Estimation of radial distortion using local spectra of planar textures","authors":"Benjamin Spitschan, J. Ostermann","doi":"10.23919/MVA.2017.7986903","DOIUrl":"https://doi.org/10.23919/MVA.2017.7986903","url":null,"abstract":"A novel self-calibration method for estimation of radial lens distortion is proposed. It requires only a single image of a textured plane that may have arbitrary orientation with respect to the camera. A frequency-based approach is used to estimate the perspective and non-linear lens distortions that planar textures are subject to when projected to a camera image plane. The texture is only required to be homogeneous and may exhibit a high amount of stochastic content. For this purpose, we derive the relationship between the local spatial frequencies of the texture and those of the image. In a joint optimization, both the rotation matrix and the radial distortion are subsequently estimated. Results show that with appropriate textures, a mean reprojection error of 9.76 · 10−5 relative to the picture width is achieved. In addition, the method is robust to image corruption by noise.","PeriodicalId":193716,"journal":{"name":"2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123196898","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
Robust markers for visual navigation using Reed-Solomon codes 使用Reed-Solomon代码的视觉导航稳健标记
2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) Pub Date : 2017-05-01 DOI: 10.23919/MVA.2017.7986900
J. Gubbi, N. Sandeep, K. P. Reddy, P. Balamuralidhar
{"title":"Robust markers for visual navigation using Reed-Solomon codes","authors":"J. Gubbi, N. Sandeep, K. P. Reddy, P. Balamuralidhar","doi":"10.23919/MVA.2017.7986900","DOIUrl":"https://doi.org/10.23919/MVA.2017.7986900","url":null,"abstract":"Indoor navigation of unmanned vehicles in GPS denied environment is challenging but a necessity in many real-world applications. Although fully autonomous indoor navigation has been shown to work using simultaneous localization and mapping (SLAM), its accuracy and robustness are inadequate for commercial applications. A semi-autonomous approach is an option for indoor navigation can be achieved using visual markers such as ArUco. The errors caused by motion of robots, visual artifacts due to change in environmental conditions and other occlusion will impact the reliability of visual markers. In this paper, a new robust visual marker based on ArUco with error detection and correction capability is proposed using Reed-Solomon codes. A dictionary of 50 symbols is generated and tested under different conditions with good results in detection and identification.","PeriodicalId":193716,"journal":{"name":"2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115340832","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: 2
A fast sparse reconstruction approach for high resolution image-based object surface anomaly detection 基于图像的高分辨率目标表面异常检测的快速稀疏重建方法
2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) Pub Date : 2017-05-01 DOI: 10.23919/MVA.2017.7986761
Woon Huei Chai, S. Ho, C. Goh, L. Chia, Hiok Chai Quek
{"title":"A fast sparse reconstruction approach for high resolution image-based object surface anomaly detection","authors":"Woon Huei Chai, S. Ho, C. Goh, L. Chia, Hiok Chai Quek","doi":"10.23919/MVA.2017.7986761","DOIUrl":"https://doi.org/10.23919/MVA.2017.7986761","url":null,"abstract":"We propose an approach to resolve two issues in a recent proposed sparse reconstruction based, anomaly detection approach as a part of automated visual inspection (AVI). The original approach needs large computation and memory for high resolution problem. To solve it, we proposed a two-step sparse reconstruction, 1) the first sparse representation of input image is estimated in a sparse reconstruction with low resolution downsampled images and 2) the high resolution residual values is generated in another sparse reconstruction with the sparse representation. The first step provides the flexibility of freely adjusting the computation and the demand of memory storage with small trade-off of detection accuracy. Moreover, an illumination adaptive threshold with morphological operators is used in the anomaly classification. Empirical results show that the proposed approach can effectively replace the original approach with better results.","PeriodicalId":193716,"journal":{"name":"2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130391167","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: 2
A surround view image generation method with low distortion for vehicle camera systems using a composite projection 一种基于复合投影的低失真车用相机系统环视图像生成方法
2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) Pub Date : 2017-05-01 DOI: 10.23919/MVA.2017.7986882
K. Nobori, N. Ukita, N. Hagita
{"title":"A surround view image generation method with low distortion for vehicle camera systems using a composite projection","authors":"K. Nobori, N. Ukita, N. Hagita","doi":"10.23919/MVA.2017.7986882","DOIUrl":"https://doi.org/10.23919/MVA.2017.7986882","url":null,"abstract":"This paper proposes a surround view image generation method for vehicle camera systems. To assist the driver during parking, a view with easy comprehension of distance and direction between the vehicle and objects is desirable. However, the conventional method of using an equidistant projection for generating a surround image of wide field of view causes image distortion, with straight lines appearing curved. This prevents the driver from correctly understanding the distance and direction of objects. Our proposed method uses a composite projection that combines two projection models: perspective projection and equidistant projection. This strategy can generate an image without distortion by using perspective projection near the vehicle and provides a wide field of view using equidistant projection. The experiments demonstrate the generation from parking scene images, using our proposed method, of a surround image with a wide field of view and no distortion near the vehicle.","PeriodicalId":193716,"journal":{"name":"2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130622198","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: 5
Field tests on flat ground of an intensity-difference based monocular visual odometry algorithm for planetary rovers 基于强度差的行星漫游者单目视觉里程计算法的平坦地面现场试验
2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) Pub Date : 2017-05-01 DOI: 10.23919/MVA.2017.7986826
G. Martinez
{"title":"Field tests on flat ground of an intensity-difference based monocular visual odometry algorithm for planetary rovers","authors":"G. Martinez","doi":"10.23919/MVA.2017.7986826","DOIUrl":"https://doi.org/10.23919/MVA.2017.7986826","url":null,"abstract":"In this contribution, the experimental results of testing a monocular visual odometry algorithm in a real rover platform over flat terrain for localization in outdoor sunlit conditions are presented. The algorithm computes the three-dimensional (3D) position of the rover by integrating its motion over time. The motion is directly estimated by maximizing a likelihood function that is the natural logarithm of the conditional probability of intensity differences measured at different observation points between consecutive images. It does not requiere as an intermediate step to determine the optical flow or establish correspondences. The images are captured by a monocular video camera that has been mounted on the rover looking to one side tilted downwards to the planet's surface. Most of the experiments were conducted under severe global illumination changes. Comparisons with ground truth data have shown an average absolute position error of 0.9% of distance traveled with an average processing time per image of 0.06 seconds.","PeriodicalId":193716,"journal":{"name":"2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130107167","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
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