This paper presents a unified recognition and stereo vision system which locates objects and determines their distances and sizes given stereo video input. Unlike other such systems, the recognition stage precedes and provides input to stereo processing. Model-based recognition is accomplished in two stages. The first stage seeks feature matches by comparing the absolute orientation, relative orientation and relative length of each image and model segments to find matching chains of segments. The second stage verifies candidate matches by comparing the relative locations of matched image features and corresponding model features. Models are generated semi-automatically from images of the desired objects. In addition to providing distance estimates, feature-based stereo information is used to disambiguate multiple or questionable matches. Although quite general, the system is described in the context of its motivating task of assessing the size of sea-cage salmon non-invasively.<>
{"title":"A unified recognition and stereo vision system for size assessment of fish","authors":"A. Naiberg, J. Little","doi":"10.1109/ACV.1994.341282","DOIUrl":"https://doi.org/10.1109/ACV.1994.341282","url":null,"abstract":"This paper presents a unified recognition and stereo vision system which locates objects and determines their distances and sizes given stereo video input. Unlike other such systems, the recognition stage precedes and provides input to stereo processing. Model-based recognition is accomplished in two stages. The first stage seeks feature matches by comparing the absolute orientation, relative orientation and relative length of each image and model segments to find matching chains of segments. The second stage verifies candidate matches by comparing the relative locations of matched image features and corresponding model features. Models are generated semi-automatically from images of the desired objects. In addition to providing distance estimates, feature-based stereo information is used to disambiguate multiple or questionable matches. Although quite general, the system is described in the context of its motivating task of assessing the size of sea-cage salmon non-invasively.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121301215","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}
This work presents a Computer Vision system for road boundary detection in automotive applications. Images are processed by a multiresolution algorithm, driven by a-priori knowledge through a top-down control. In order to face the hard real-time constraints of automotive tasks, a special purpose massively parallel computer architecture, PAPRICA, has been developed. The whole system is currently operative on MOB-LAB mobile laboratory: a land vehicle integrating the results of the activities of the Italian PROMETHEUS units. The basis of the algorithm is discussed using the formal tools of mathematical morphology, while the choice of the computing architecture and of the computational paradigm is explained. The generality of the presented approach allows its use also to solve similar problems, namely to detect features exploiting a long-distance correlation, such as the road boundaries in vehicular applications.<>
{"title":"A morphological model-driven approach to real-time road boundary detection for vision-based automotive systems","authors":"A. Broggi, S. Bertè","doi":"10.1109/ACV.1994.341330","DOIUrl":"https://doi.org/10.1109/ACV.1994.341330","url":null,"abstract":"This work presents a Computer Vision system for road boundary detection in automotive applications. Images are processed by a multiresolution algorithm, driven by a-priori knowledge through a top-down control. In order to face the hard real-time constraints of automotive tasks, a special purpose massively parallel computer architecture, PAPRICA, has been developed. The whole system is currently operative on MOB-LAB mobile laboratory: a land vehicle integrating the results of the activities of the Italian PROMETHEUS units. The basis of the algorithm is discussed using the formal tools of mathematical morphology, while the choice of the computing architecture and of the computational paradigm is explained. The generality of the presented approach allows its use also to solve similar problems, namely to detect features exploiting a long-distance correlation, such as the road boundaries in vehicular applications.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126103038","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}
M. Tistarelli, Francesco Guarnotta, Danilo Rizzieri, Federico Tarocchi
In this paper the problem of automated control of a road vehicle is addressed. In particular, a system is presented where optical flow techniques are applied to monitor overtaking maneuvers of other vehicles coming from the rear of the car. During car driving, most visual information is conveyed by the motion perceived within the visual field. The proposed approach for overtaking control is based on the computation of the optical flow (or the normal flow) from an image stream acquired from a camera sensor mounted on board of the vehicle. The method applies for a road vehicle and constitutes a building block of a software and hardware architecture devised to provide helpful information as an aid to the driver. Several experiments are presented from real image sequences.<>
{"title":"Application of optical flow for automated overtaking control","authors":"M. Tistarelli, Francesco Guarnotta, Danilo Rizzieri, Federico Tarocchi","doi":"10.1109/ACV.1994.341295","DOIUrl":"https://doi.org/10.1109/ACV.1994.341295","url":null,"abstract":"In this paper the problem of automated control of a road vehicle is addressed. In particular, a system is presented where optical flow techniques are applied to monitor overtaking maneuvers of other vehicles coming from the rear of the car. During car driving, most visual information is conveyed by the motion perceived within the visual field. The proposed approach for overtaking control is based on the computation of the optical flow (or the normal flow) from an image stream acquired from a camera sensor mounted on board of the vehicle. The method applies for a road vehicle and constitutes a building block of a software and hardware architecture devised to provide helpful information as an aid to the driver. Several experiments are presented from real image sequences.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126947909","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}
Leukocytes are divided into classes. Their automatic classification is accomplished by means of site functions, based on two measuring functions defined expressly for taking into account the specific morphological features of the cell classes. A successful experimentation on 45 cells is reported. The original contribution resides in the use of this new geometrical-topological technique, size theory, so confirming its suitableness for recognition of natural objects.<>
{"title":"Leukocyte classifications by size functions","authors":"M. Ferri, S. Lombardini, Clemente Pallotti","doi":"10.1109/ACV.1994.341314","DOIUrl":"https://doi.org/10.1109/ACV.1994.341314","url":null,"abstract":"Leukocytes are divided into classes. Their automatic classification is accomplished by means of site functions, based on two measuring functions defined expressly for taking into account the specific morphological features of the cell classes. A successful experimentation on 45 cells is reported. The original contribution resides in the use of this new geometrical-topological technique, size theory, so confirming its suitableness for recognition of natural objects.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125657765","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}
F. Grimm, X. Fàbregas, H. Bunke, Stefan Weiss, Reto Wittwer
This paper describes a system for the interpretation of thyroid scintigrams. In addition to low level image processing methods like smoothing, segmentation, and approximation, knowledge-based methods are used in order to match features extracted from the scintigram with other informations obtained during diagnostic examination. The system has been applied on a series of real patient cases and shown good performance.<>
{"title":"Knowledge-based interpretation of thyroid scintigrams","authors":"F. Grimm, X. Fàbregas, H. Bunke, Stefan Weiss, Reto Wittwer","doi":"10.1109/ACV.1994.341315","DOIUrl":"https://doi.org/10.1109/ACV.1994.341315","url":null,"abstract":"This paper describes a system for the interpretation of thyroid scintigrams. In addition to low level image processing methods like smoothing, segmentation, and approximation, knowledge-based methods are used in order to match features extracted from the scintigram with other informations obtained during diagnostic examination. The system has been applied on a series of real patient cases and shown good performance.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133554925","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}
We present a binocular gaze holding method of an object which is moving in the complicated scene with the Active Stereo Vision System. The system uses a binocular vision robot, which can simulate the human eye movements. Holding gaze on a target object with the controlled cameras keeps the target's stereo disparity small, and simplifies the visual processing to locate the target for pursuit control. The novel point of our tracking method is the disparity-based segmentation method of the target object. The method utilizes a zero disparity filter (ZDF) and correlation to separate the target object with small disparity from distracting background. Furthermore, using the correlation method to estimate stereo disparity makes it possible to fixate on a surface of the target object. We show the experimental results with the complicated scene to demonstrate the effectiveness of the proposed method.<>
{"title":"Binocular gaze holding of a moving object with the active stereo vision system","authors":"Maki Tanaka, N. Maru, F. Miyazaki","doi":"10.1109/ACV.1994.341318","DOIUrl":"https://doi.org/10.1109/ACV.1994.341318","url":null,"abstract":"We present a binocular gaze holding method of an object which is moving in the complicated scene with the Active Stereo Vision System. The system uses a binocular vision robot, which can simulate the human eye movements. Holding gaze on a target object with the controlled cameras keeps the target's stereo disparity small, and simplifies the visual processing to locate the target for pursuit control. The novel point of our tracking method is the disparity-based segmentation method of the target object. The method utilizes a zero disparity filter (ZDF) and correlation to separate the target object with small disparity from distracting background. Furthermore, using the correlation method to estimate stereo disparity makes it possible to fixate on a surface of the target object. We show the experimental results with the complicated scene to demonstrate the effectiveness of the proposed method.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115635443","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}
An analysis system design based on experience with a successful application in the field of inspection and calibration of an analog display measuring instrument is presented in this paper. First the measuring instrument is divided into its primitiva, defining the a priori known parameter of the primitiva: shape, relative position and size. According to the shape of the primitiva pattern recognition algorithms are used to detect the primitiva in intensity images. These independent detection algorithms are then grouped into a detecting order with respect to efficiency. Following a discussion of the general design of the detecting algorithm, specific constraints of the application and the industrial environment are considered in order to refine the general design to an applicable and efficient device by modifying both hardware and software configuration depending on the given constraints. Finally, results of the implementation of the algorithm and the constructed image acquisition device are discussed.<>
{"title":"Application constraints in the design of an automatic reading device for analog display instruments","authors":"Robert Sablatnig, W. Kropatsch","doi":"10.1109/ACV.1994.341310","DOIUrl":"https://doi.org/10.1109/ACV.1994.341310","url":null,"abstract":"An analysis system design based on experience with a successful application in the field of inspection and calibration of an analog display measuring instrument is presented in this paper. First the measuring instrument is divided into its primitiva, defining the a priori known parameter of the primitiva: shape, relative position and size. According to the shape of the primitiva pattern recognition algorithms are used to detect the primitiva in intensity images. These independent detection algorithms are then grouped into a detecting order with respect to efficiency. Following a discussion of the general design of the detecting algorithm, specific constraints of the application and the industrial environment are considered in order to refine the general design to an applicable and efficient device by modifying both hardware and software configuration depending on the given constraints. Finally, results of the implementation of the algorithm and the constructed image acquisition device are discussed.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128953467","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}
A model based approach to monocular image sequence analysis of road traffic scenes is presented. Within this framework a vision system for applications like autonomous driving and collision avoidance was developed. The approach takes part in problems of selective and active vision. The fully automatic system MOSAIK recognizes and describes all visual vehicles on or near the road. It solves the problem to compute a robust scene description under egomotion nearly in realtime on a standard monoprocessor workstation. MOSAIK has been tested by using typical German 'Autobahn' and road scenes. This paper describes the vision approach and the interaction of vehicle recognition and tracking and the influence of attention control.<>
{"title":"A robust cognitive approach to traffic scene analysis","authors":"D. Wetzel, H. Niemann, S. Richter","doi":"10.1109/ACV.1994.341291","DOIUrl":"https://doi.org/10.1109/ACV.1994.341291","url":null,"abstract":"A model based approach to monocular image sequence analysis of road traffic scenes is presented. Within this framework a vision system for applications like autonomous driving and collision avoidance was developed. The approach takes part in problems of selective and active vision. The fully automatic system MOSAIK recognizes and describes all visual vehicles on or near the road. It solves the problem to compute a robust scene description under egomotion nearly in realtime on a standard monoprocessor workstation. MOSAIK has been tested by using typical German 'Autobahn' and road scenes. This paper describes the vision approach and the interaction of vehicle recognition and tracking and the influence of attention control.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134404684","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}
M. W. Hansen, P. Anandan, Kristin J. Dana, G. V. D. Wal, P. Burt
We describe a real-time system designed to construct a stable view of a scene through aligning images of an incoming video stream and dynamically constructing an image mosaic. This system uses a video processing unit developed by the David Sarnoff Research Center called the Vision Front End (VFE-100) for the pyramid-based image processing tasks required to implement this process. This paper includes a description of the multiresolution coarse-to-fine image registration strategy, the techniques used for mosaic construction, the implementation of this process on the VFE-100 system, and experimental results showing image mosaics constructed with the VFE-100.<>
{"title":"Real-time scene stabilization and mosaic construction","authors":"M. W. Hansen, P. Anandan, Kristin J. Dana, G. V. D. Wal, P. Burt","doi":"10.1109/ACV.1994.341288","DOIUrl":"https://doi.org/10.1109/ACV.1994.341288","url":null,"abstract":"We describe a real-time system designed to construct a stable view of a scene through aligning images of an incoming video stream and dynamically constructing an image mosaic. This system uses a video processing unit developed by the David Sarnoff Research Center called the Vision Front End (VFE-100) for the pyramid-based image processing tasks required to implement this process. This paper includes a description of the multiresolution coarse-to-fine image registration strategy, the techniques used for mosaic construction, the implementation of this process on the VFE-100 system, and experimental results showing image mosaics constructed with the VFE-100.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"317 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132068929","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}
Traffic statistics desired by road engineers and planners, and "traffic warning" systems demand real-time performance which precludes the use of batch processing. We apply recent real-time trading techniques along with scene specific tuning of the dynamics to enable the tracker to accurately predict target location and thus reduce the amount of search and/or image processing required. The benefits of learning dynamics for accurate prediction are speed-our tracker operates at frame rate-and smoothing of vibration. Initial calibration of the projective relationship between the image and ground planes enables metric information to be derived from the image positions and velocities without full camera calibration. Results are presented on real-world traffic scenes showing the tracker to be both fast and robust to vibrations which are inevitable in traffic locations.<>
{"title":"Real-time traffic monitoring","authors":"N. Ferrier, S. Rowe, A. Blake","doi":"10.1109/ACV.1994.341292","DOIUrl":"https://doi.org/10.1109/ACV.1994.341292","url":null,"abstract":"Traffic statistics desired by road engineers and planners, and \"traffic warning\" systems demand real-time performance which precludes the use of batch processing. We apply recent real-time trading techniques along with scene specific tuning of the dynamics to enable the tracker to accurately predict target location and thus reduce the amount of search and/or image processing required. The benefits of learning dynamics for accurate prediction are speed-our tracker operates at frame rate-and smoothing of vibration. Initial calibration of the projective relationship between the image and ground planes enables metric information to be derived from the image positions and velocities without full camera calibration. Results are presented on real-world traffic scenes showing the tracker to be both fast and robust to vibrations which are inevitable in traffic locations.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131677121","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}
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