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Applied Imaging Pattern Recognition最新文献

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Feature-based technique for automated image registration of the brain 基于特征的脑图像自动配准技术
Applied Imaging Pattern Recognition Pub Date : 2000-05-05 DOI: 10.1117/12.384878
L. Hsu, M. Loew
{"title":"Feature-based technique for automated image registration of the brain","authors":"L. Hsu, M. Loew","doi":"10.1117/12.384878","DOIUrl":"https://doi.org/10.1117/12.384878","url":null,"abstract":"In this paper, we present an automated multi-modality registration algorithm based on hierarchical feature extraction. The approach, which has not ben used previously, can be divided into two distinct stages: feature extraction and geometric matching. Two kinds of corresponding features - edge and surface - are extracted hierarchically from various image modalities. The registration then is performed using least-squares matching of the automatically extracted features. Both the robustness and accuracy of feature extraction and geometric marching steps are evaluated using simulated and patient images. The preliminary results show the error is on the average of one voxel. We have shown the proposed 3D registration algorithm provides a simple and fast method for automatic registering of MR-to-CT and MR-to- PET image modalities. Our results are comparable to other techniques and require no user interaction.","PeriodicalId":354140,"journal":{"name":"Applied Imaging Pattern Recognition","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128449397","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
New large-scale 3D laser scanning, modeling, and visualization technology provides advanced capabilities for scene reconstruction and interpretation 新的大规模3D激光扫描、建模和可视化技术为场景重建和解释提供了先进的能力
Applied Imaging Pattern Recognition Pub Date : 2000-05-05 DOI: 10.1117/12.384862
Geoffrey L. Jacobs
{"title":"New large-scale 3D laser scanning, modeling, and visualization technology provides advanced capabilities for scene reconstruction and interpretation","authors":"Geoffrey L. Jacobs","doi":"10.1117/12.384862","DOIUrl":"https://doi.org/10.1117/12.384862","url":null,"abstract":"The task of accurately reconstructing scenes for interpretation has frequently proved problematic. Conventional methods of reconstructing 3D scenes often involve sacrificial trade-offs among several parameters: (1) completeness of scene reconstruction, (2) geometric accuracy, (3) time for capturing information and creating 3D computer models, (4) the need to not disturb the original scene during data capture, and (5) cost. A compelling, new technology, Large-scale 3D Laser Scanning, Modeling and Visualization, promises to have a major impact on the field by delivering 3D computer models of scenes that are both highly accurate and complete, in a more timely, and cost- effective manner.","PeriodicalId":354140,"journal":{"name":"Applied Imaging Pattern Recognition","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123312128","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
MultiVIS: a web-based interactive remote visualization environment and navigable volume imagemap system MultiVIS:一个基于web的交互式远程可视化环境和可导航的卷图像地图系统
Applied Imaging Pattern Recognition Pub Date : 2000-05-05 DOI: 10.1117/12.384871
M. Doyle, G. Klein, F. Hussaini, M. Pescitelli
{"title":"MultiVIS: a web-based interactive remote visualization environment and navigable volume imagemap system","authors":"M. Doyle, G. Klein, F. Hussaini, M. Pescitelli","doi":"10.1117/12.384871","DOIUrl":"https://doi.org/10.1117/12.384871","url":null,"abstract":"This work represents the convergent evolution of a number of technologies and research 'threads'. A project called MetaMAP, which developed early hypermedia imagemap technology, dates back to 1986. Work on creating a new paradigm for doing client-server visualization over the Internet began in 1992. Another major project began in 1993 to turn the Web into a platform for interactive applications. A project to develop multidimensional imagemap technology began in 1995. Finally, work on a scalable computational server architecture called 'Dark Iron' began in 1997. The MultiVIS project represents the intersection of these various research efforts to create a new kind of navigable knowledge space that leverages the advantages of each of its constituent technologies.","PeriodicalId":354140,"journal":{"name":"Applied Imaging Pattern Recognition","volume":"3905 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130178304","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
OpenSkies: a commercial 3D distributed visualization and simulation toolkit OpenSkies:一个商业3D分布式可视化和仿真工具包
Applied Imaging Pattern Recognition Pub Date : 2000-05-05 DOI: 10.1117/12.384872
Paul Cobb, C. Jacobus, D. Haanpaa
{"title":"OpenSkies: a commercial 3D distributed visualization and simulation toolkit","authors":"Paul Cobb, C. Jacobus, D. Haanpaa","doi":"10.1117/12.384872","DOIUrl":"https://doi.org/10.1117/12.384872","url":null,"abstract":"A growing need for more advanced training capabilities and the proliferation of government standards into the commercial market has inspired Cybernet to create an advanced, distributed 3D Simulation Toolkit. This system, called OpenSkies, is a truly open, realistic distributed system for 3D visualization and simulation. One of the main strengths of OpenSkies is its capability for data collection and analysis. Cybernet's Data Collection and Analysis Environment is closely integrated with OpenSkies to produce a unique, quantitative, performance-based measurement system. This system provides the capability for training students and operators on any complex equipment or system that can be created in a simulated world. OpenSkies is based on the military standard HLA networking architecture. This architecture allows thousands of users to interact in the same world across the Internet. Cybernet's OpenSkies simulation system brings the power and versatility of the OpenGL programming API to the simulation and gaming worlds. On top of this, Cybernet has developed an open architecture that allows the developer to produce almost any kind of new technique in their simulation. Overall, these capabilities deliver a versatile and comprehensive toolkit for simulation and distributed visualization.","PeriodicalId":354140,"journal":{"name":"Applied Imaging Pattern Recognition","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116508973","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
Forensic 3D scene reconstruction 法医3D场景重建
Applied Imaging Pattern Recognition Pub Date : 2000-05-05 DOI: 10.1117/12.384885
C. Little, D. Small, Ralph Peters, J. Rigdon
{"title":"Forensic 3D scene reconstruction","authors":"C. Little, D. Small, Ralph Peters, J. Rigdon","doi":"10.1117/12.384885","DOIUrl":"https://doi.org/10.1117/12.384885","url":null,"abstract":"Traditionally law enforcement agencies have relied on basic measurement and imaging tools, such as tape measures and cameras, in recording a crime scene. A disadvantage of these methods is that they are slow and cumbersome. The development of a portable system that can rapidly record a crime scene with current camera imaging, 3D geometric surface maps, and contribute quantitative measurements such as accurate relative positioning of crime scene objects, would be an asset to law enforcement agents in collecting and recording significant forensic data. The purpose of this project is to develop a fieldable prototype of a fast, accurate, 3D measurement and imaging system that would support law enforcement agents to quickly document and accurately record a crime scene.","PeriodicalId":354140,"journal":{"name":"Applied Imaging Pattern Recognition","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133762411","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
Registration and integration of multisensor data for photorealistic scene reconstruction 面向逼真场景重建的多传感器数据配准与集成
Applied Imaging Pattern Recognition Pub Date : 2000-05-05 DOI: 10.1117/12.384860
Faysal Boughorbal, D. Page, C. Dumont, M. Abidi
{"title":"Registration and integration of multisensor data for photorealistic scene reconstruction","authors":"Faysal Boughorbal, D. Page, C. Dumont, M. Abidi","doi":"10.1117/12.384860","DOIUrl":"https://doi.org/10.1117/12.384860","url":null,"abstract":"In this paper, we present a method for automatically registering a 3D range image and a 2D color image using the (chi) 2-similarity metric. The goal of this registration is to allow the reconstruction of a scene using multi-sensor information. Traditional registration algorithms use invariant image features to drive the registration process. This approach limits the applicability to multi-modal data since features of interest may not appear in each modality. However, the (chi) 2-similarity metric is an intensity- based approach that has interesting multi-modal characteristics. We explore this metric as a mechanism to govern the registration search. Using range data from a Perceptron laser camera and color data form a Kodak digital camera, we present result using this automatic registration with the (chi) 2-similarity metric.","PeriodicalId":354140,"journal":{"name":"Applied Imaging Pattern Recognition","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130744562","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: 14
ViA: a perceptual visualization assistant ViA:一个感知可视化助手
Applied Imaging Pattern Recognition Pub Date : 2000-05-05 DOI: 10.1117/12.384859
C. Healey, R. St. Amant, Mahmoud Elhaddad
{"title":"ViA: a perceptual visualization assistant","authors":"C. Healey, R. St. Amant, Mahmoud Elhaddad","doi":"10.1117/12.384859","DOIUrl":"https://doi.org/10.1117/12.384859","url":null,"abstract":"This paper describes an automated visualized assistant called ViA. ViA is designed to help users construct perceptually optical visualizations to represent, explore, and analyze large, complex, multidimensional datasets. We have approached this problem by studying what is known about the control of human visual attention. By harnessing the low-level human visual system, we can support our dual goals of rapid and accurate visualization. Perceptual guidelines that we have built using psychophysical experiments form the basis for ViA. ViA uses modified mixed-initiative planning algorithms from artificial intelligence to search of perceptually optical data attribute to visual feature mappings. Our perceptual guidelines are integrated into evaluation engines that provide evaluation weights for a given data-feature mapping, and hints on how that mapping might be improved. ViA begins by asking users a set of simple questions about their dataset and the analysis tasks they want to perform. Answers to these questions are used in combination with the evaluation engines to identify and intelligently pursue promising data-feature mappings. The result is an automatically-generated set of mappings that are perceptually salient, but that also respect the context of the dataset and users' preferences about how they want to visualize their data.","PeriodicalId":354140,"journal":{"name":"Applied Imaging Pattern Recognition","volume":"109 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131587521","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: 36
Four-dimensional ATR processing and visualization 四维ATR处理和可视化
Applied Imaging Pattern Recognition Pub Date : 2000-05-05 DOI: 10.1117/12.384863
M. Berlin
{"title":"Four-dimensional ATR processing and visualization","authors":"M. Berlin","doi":"10.1117/12.384863","DOIUrl":"https://doi.org/10.1117/12.384863","url":null,"abstract":"Contemporary automatic target recognition (ATR) technology programs require reasoning not only in space but also across time and sensor type. If contemporary scale-space techniques are also considered then up to a 5D processing regime is required. Algorithm development under such conditions will greatly benefit from advanced visualization tools. In this paper, examples of 4D processing for ATR will be given using a prototype tool developed in Java 1.2. Limitations of current tools and software for visualization of ATR applications will be addressed. Future tools to accelerate the algorithm development process will also be discussed.","PeriodicalId":354140,"journal":{"name":"Applied Imaging Pattern Recognition","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125479549","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
Extracting invariant features of the human face from 3D range data 从三维距离数据中提取人脸的不变特征
Applied Imaging Pattern Recognition Pub Date : 2000-05-05 DOI: 10.1117/12.384873
Shoude Chang, M. Rioux, C. Grover
{"title":"Extracting invariant features of the human face from 3D range data","authors":"Shoude Chang, M. Rioux, C. Grover","doi":"10.1117/12.384873","DOIUrl":"https://doi.org/10.1117/12.384873","url":null,"abstract":"The surface of the human face can be represented by a set of facets. The Phase Fourier Transform (PFT) can be used to transform a facet in the space domain to a peak in the frequency domain. The position and the distribution of the peak represent the orientation and shape of the facet respectively. The PFT of the human face provides a new signature of the face. The intensity of the PFT is invariant to the shift and out-of-plane rotation within a certain angle. It is also scale invariant within a certain range. We have used Circular Harmonic m-r filtering to achieve the in- plane partial rotation invariance. The recognition decision is based on the intensity and performance of the correlation peak.","PeriodicalId":354140,"journal":{"name":"Applied Imaging Pattern Recognition","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121321904","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
Monitoring human and vehicle activities using airborne video 使用机载视频监控人类和车辆活动
Applied Imaging Pattern Recognition Pub Date : 2000-05-05 DOI: 10.1117/12.384868
Ross Cutler, C. Shekhar, B. Burns, R. Chellappa, R. Bolles, L. Davis
{"title":"Monitoring human and vehicle activities using airborne video","authors":"Ross Cutler, C. Shekhar, B. Burns, R. Chellappa, R. Bolles, L. Davis","doi":"10.1117/12.384868","DOIUrl":"https://doi.org/10.1117/12.384868","url":null,"abstract":"Ongoing work in Activity Monitoring (AM) for the Airborne Video Surveillance (AVS) project is described. The goal for AM is to recognize activities of interest involving humans and vehicles using airborne video. AM consists of three major components: (1) moving object detection, tracking, and classification; (2) image to site-model registration; (3) activity recognition. Detecting and tracking humans and vehicles form airborne video is a challenging problem due to image noise, low GSD, poor contrast, motion parallax, motion blur, and camera blur, and camera jitter. We use frame-to- frame affine-warping stabilization and temporally integrated intensity differences to detect independent motion. Moving objects are initially tracked using nearest-neighbor correspondence, followed by a greedy method that favors long track lengths and assumes locally constant velocity. Object classification is based on object size, velocity, and periodicity of motion. Site-model registration uses GPS information and camera/airplane orientations to provide an initial geolocation with +/- 100m accuracy at an elevation of 1000m. A semi-automatic procedure is utilized to improve the accuracy to +/- 5m. The activity recognition component uses the geolocated tracked objects and the site-model to detect pre-specified activities, such as people entering a forbidden area and a group of vehicles leaving a staging area.","PeriodicalId":354140,"journal":{"name":"Applied Imaging Pattern Recognition","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126715866","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: 18
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