Pub Date : 1994-11-11DOI: 10.1109/MNRAO.1994.346258
V. Burdin, C. Roux, E. Stindel, C. Lefevre
The purpose of this work is to study the human movements and more precisely the rotation, of the forearm, called the prosupination motion. From medical papers which have analysed the kinematics aspects, we deduce a computer simulation of the prosupination motion. We evaluate the magnitude of the motion detecting automatically collisions between the two bones during the movement. The collision detection technique allows us to deduce the influence of the bone morphology (malformations) on the magnitude of the prosupination motion.<>
{"title":"Study of 3-D human movements: influence of the forearm bone morphology on the magnitude of the prosupination motion","authors":"V. Burdin, C. Roux, E. Stindel, C. Lefevre","doi":"10.1109/MNRAO.1994.346258","DOIUrl":"https://doi.org/10.1109/MNRAO.1994.346258","url":null,"abstract":"The purpose of this work is to study the human movements and more precisely the rotation, of the forearm, called the prosupination motion. From medical papers which have analysed the kinematics aspects, we deduce a computer simulation of the prosupination motion. We evaluate the magnitude of the motion detecting automatically collisions between the two bones during the movement. The collision detection technique allows us to deduce the influence of the bone morphology (malformations) on the magnitude of the prosupination motion.<<ETX>>","PeriodicalId":336218,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects","volume":"10795 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125044160","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}
Pub Date : 1994-11-11DOI: 10.1109/MNRAO.1994.346259
K. Takahashi, S. Seki, E. Kojima, R. Oka
This paper presents a method for recognizing dexterous manipulation actions that we usually perform using our hands. Our method is based on model representation using spatio-temporal vector fields and a spotting algorithm that gives segmentation-free and frame-by-frame recognition. We propose a multiview motion model that is composed of several standard sequence patterns made from different viewpoints. Results indicate that our method recognizes dexterous manipulations correctly, even if the viewing direction of the input images deviates from those of standard sequence patterns.<>
{"title":"Recognition of dexterous manipulations from time-varying images","authors":"K. Takahashi, S. Seki, E. Kojima, R. Oka","doi":"10.1109/MNRAO.1994.346259","DOIUrl":"https://doi.org/10.1109/MNRAO.1994.346259","url":null,"abstract":"This paper presents a method for recognizing dexterous manipulation actions that we usually perform using our hands. Our method is based on model representation using spatio-temporal vector fields and a spotting algorithm that gives segmentation-free and frame-by-frame recognition. We propose a multiview motion model that is composed of several standard sequence patterns made from different viewpoints. Results indicate that our method recognizes dexterous manipulations correctly, even if the viewing direction of the input images deviates from those of standard sequence patterns.<<ETX>>","PeriodicalId":336218,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126906230","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}
Pub Date : 1994-11-11DOI: 10.1109/MNRAO.1994.346237
N. Sharp, E. Hancock
This paper describes a novel feature tracking method. It is based on an inter-frame relaxation technique. This method combines intra-frame and inter-frame constraints on the behaviour of acceptable contour structure. The intra-frame information is represented by both a dictionary of local contour structure and a statistical model of the response of a set of directional feature detection operators. The inter-frame ingredient represents the novel modelling component; it is encapsulated by an implicit model of the underlying surface structure of 3D feature points. The model is represented in terms of a series of unimodal probability densities whose single parameter is the inter-frame distance. The initial probabilities in our relaxation scheme effectively combine distributions describing the statistical uncertainties in the position and feature characteristics of multiframe contours; these probabilities are refined in the light of the dictionary to produce consistent contours.<>
{"title":"Contour tracking by multi-frame relaxation","authors":"N. Sharp, E. Hancock","doi":"10.1109/MNRAO.1994.346237","DOIUrl":"https://doi.org/10.1109/MNRAO.1994.346237","url":null,"abstract":"This paper describes a novel feature tracking method. It is based on an inter-frame relaxation technique. This method combines intra-frame and inter-frame constraints on the behaviour of acceptable contour structure. The intra-frame information is represented by both a dictionary of local contour structure and a statistical model of the response of a set of directional feature detection operators. The inter-frame ingredient represents the novel modelling component; it is encapsulated by an implicit model of the underlying surface structure of 3D feature points. The model is represented in terms of a series of unimodal probability densities whose single parameter is the inter-frame distance. The initial probabilities in our relaxation scheme effectively combine distributions describing the statistical uncertainties in the position and feature characteristics of multiframe contours; these probabilities are refined in the light of the dictionary to produce consistent contours.<<ETX>>","PeriodicalId":336218,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114882246","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}
Pub Date : 1994-11-11DOI: 10.1109/MNRAO.1994.346239
T. Denney, Jerry L Prince
An important application of deformable motion estimation theory is the estimation of heart motion from tagged magnetic resonance image sequences. In tagged MR images, the heart appears with a spatially encoded pattern that moves with the tissue. The position of the tag pattern in each frame of the image sequence can be used to obtain sparse measurements of the heart's 3D displacement field. In this paper, we propose a method for estimating a dense displacement field from sparse displacement measurements that is based on a multidimensional stochastic model for the smoothness and divergence of the displacement field and uses the Fisher estimation framework. The main feature of this method is that the displacement field model and the resulting estimate equation are defined only on the irregular domain of the myocardium. Simulation results are presented that demonstrate the accuracy of our method and show the effect of the tag pattern on the estimation error.<>
{"title":"3D displacement field reconstruction on an irregular domain from planar tagged cardiac MR images","authors":"T. Denney, Jerry L Prince","doi":"10.1109/MNRAO.1994.346239","DOIUrl":"https://doi.org/10.1109/MNRAO.1994.346239","url":null,"abstract":"An important application of deformable motion estimation theory is the estimation of heart motion from tagged magnetic resonance image sequences. In tagged MR images, the heart appears with a spatially encoded pattern that moves with the tissue. The position of the tag pattern in each frame of the image sequence can be used to obtain sparse measurements of the heart's 3D displacement field. In this paper, we propose a method for estimating a dense displacement field from sparse displacement measurements that is based on a multidimensional stochastic model for the smoothness and divergence of the displacement field and uses the Fisher estimation framework. The main feature of this method is that the displacement field model and the resulting estimate equation are defined only on the irregular domain of the myocardium. Simulation results are presented that demonstrate the accuracy of our method and show the effect of the tag pattern on the estimation error.<<ETX>>","PeriodicalId":336218,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124154990","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}
Pub Date : 1994-11-11DOI: 10.1109/MNRAO.1994.346235
R. Furukawa, M. Imai, T. Uno
Determining motion of objects is a very important and difficult problem. Many researches have been studied in this field. We previously presented a new model, named Active Tubes, to find motion of non-rigid objects from an image sequence. Active Tubes analyzes the temporal context in a spatio-temporal solid using an energy minimizing model like Snakes. You can consider it as a kind of accumulation of Snakes along the time axis. In the former paper, we used greedy algorithm to converge Active Tubes. In, this paper, we point out greedy algorithm's weakness to noise, and propose an extended algorithm to deform Active Tubes. The new algorithm is as fast as greedy algorithm and more robust from noise.<>
{"title":"Robust algorithm for motion analysis based on Active Tubes","authors":"R. Furukawa, M. Imai, T. Uno","doi":"10.1109/MNRAO.1994.346235","DOIUrl":"https://doi.org/10.1109/MNRAO.1994.346235","url":null,"abstract":"Determining motion of objects is a very important and difficult problem. Many researches have been studied in this field. We previously presented a new model, named Active Tubes, to find motion of non-rigid objects from an image sequence. Active Tubes analyzes the temporal context in a spatio-temporal solid using an energy minimizing model like Snakes. You can consider it as a kind of accumulation of Snakes along the time axis. In the former paper, we used greedy algorithm to converge Active Tubes. In, this paper, we point out greedy algorithm's weakness to noise, and propose an extended algorithm to deform Active Tubes. The new algorithm is as fast as greedy algorithm and more robust from noise.<<ETX>>","PeriodicalId":336218,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128176518","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}
Pub Date : 1994-11-11DOI: 10.1109/MNRAO.1994.346246
Y. Hel-Or, M. Werman
Presents a method for the localization and interpretation of modeled objects that is general enough to cover articulated and other types of constrained models. The flexibility between components of the model are expressed as spatial constraints which are fused into the pose estimation during the interpretation process. The constraint fusion assists in obtaining a precise and stable pose of each object's component and in finding the correct interpretation. The proposed method can handle any constraint (including inequalities) between any number of different components of the model. The framework is based on Kalman filtering.<>
{"title":"Recognition and localization of articulated objects","authors":"Y. Hel-Or, M. Werman","doi":"10.1109/MNRAO.1994.346246","DOIUrl":"https://doi.org/10.1109/MNRAO.1994.346246","url":null,"abstract":"Presents a method for the localization and interpretation of modeled objects that is general enough to cover articulated and other types of constrained models. The flexibility between components of the model are expressed as spatial constraints which are fused into the pose estimation during the interpretation process. The constraint fusion assists in obtaining a precise and stable pose of each object's component and in finding the correct interpretation. The proposed method can handle any constraint (including inequalities) between any number of different components of the model. The framework is based on Kalman filtering.<<ETX>>","PeriodicalId":336218,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125965626","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}
Pub Date : 1994-11-11DOI: 10.1109/MNRAO.1994.346231
Stefano Soatto, P. Perona
A three dimensional scene can be segmented using different cues, such as boundaries, texture, motion, discontinuities of the optical flow, stereo, models for structure, etc. We investigate segmentation based upon one of these cues, namely three dimensional motion. If the scene contain transparent objects, the two dimensional (local) cues are inconsistent, since neighboring points with similar optical flow can correspond to different objects. We present a method for performing three dimensional motion-based segmentation of (possibly) transparent scenes together with recursive estimation of the motion of each independent rigid object from monocular perspective images. Our algorithm is based on a recently proposed method for rigid motion reconstruction and a validation test which allows us to initialize the scheme and detect outliers during the motion estimation procedure. The scheme is tested on challenging real and synthetic image sequences. Segmentation is performed for the Ullmann's experiment of two transparent cylinders rotating about the same axis in opposite directions.<>
{"title":"Three dimensional transparent structure segmentation and multiple 3D motion estimation from monocular perspective image sequences","authors":"Stefano Soatto, P. Perona","doi":"10.1109/MNRAO.1994.346231","DOIUrl":"https://doi.org/10.1109/MNRAO.1994.346231","url":null,"abstract":"A three dimensional scene can be segmented using different cues, such as boundaries, texture, motion, discontinuities of the optical flow, stereo, models for structure, etc. We investigate segmentation based upon one of these cues, namely three dimensional motion. If the scene contain transparent objects, the two dimensional (local) cues are inconsistent, since neighboring points with similar optical flow can correspond to different objects. We present a method for performing three dimensional motion-based segmentation of (possibly) transparent scenes together with recursive estimation of the motion of each independent rigid object from monocular perspective images. Our algorithm is based on a recently proposed method for rigid motion reconstruction and a validation test which allows us to initialize the scheme and detect outliers during the motion estimation procedure. The scheme is tested on challenging real and synthetic image sequences. Segmentation is performed for the Ullmann's experiment of two transparent cylinders rotating about the same axis in opposite directions.<<ETX>>","PeriodicalId":336218,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123309518","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}
Pub Date : 1994-11-11DOI: 10.1109/MNRAO.1994.346244
M. Penna
In this paper, we present an approach to modeling nonrigid transformations (equivalently, nonrigid surfaces) by homogeneous transformations, and we illustrate the utility of this approach by describing how we used it to study sequences of static nonrigid motions of a membrane. Experimental results are presented.<>
{"title":"Nonrigid motions as homogeneous transformations","authors":"M. Penna","doi":"10.1109/MNRAO.1994.346244","DOIUrl":"https://doi.org/10.1109/MNRAO.1994.346244","url":null,"abstract":"In this paper, we present an approach to modeling nonrigid transformations (equivalently, nonrigid surfaces) by homogeneous transformations, and we illustrate the utility of this approach by describing how we used it to study sequences of static nonrigid motions of a membrane. Experimental results are presented.<<ETX>>","PeriodicalId":336218,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129719690","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}
Pub Date : 1994-11-11DOI: 10.1109/MNRAO.1994.346263
F. Perales, J. Torres
A system for analysis and synthesis of human motion is presented. The system consists of an analysis part and a synthesis part. The analysis part can be used automatically or interactively. The automatic analysis part includes the pre-processing, modeling, matching and interpretation phases. The interactive analysis part includes the same phases but with the possibility of user supervision. We present a global overview of the whole system. The user can define a biomechanic graphical model to represent the human body in a 3D space, and use tools to perform an automatic or interactive supervised matching between the animated model and the real images to recover the motion. The synthesis part uses the results of matching process to show the motion of the human body that is shown in the real images, from any viewpoint. We use specific criteria to match walking persons from different views. Some results and images are presented.<>
{"title":"A system for human motion matching between synthetic and real images based on a biomechanic graphical model","authors":"F. Perales, J. Torres","doi":"10.1109/MNRAO.1994.346263","DOIUrl":"https://doi.org/10.1109/MNRAO.1994.346263","url":null,"abstract":"A system for analysis and synthesis of human motion is presented. The system consists of an analysis part and a synthesis part. The analysis part can be used automatically or interactively. The automatic analysis part includes the pre-processing, modeling, matching and interpretation phases. The interactive analysis part includes the same phases but with the possibility of user supervision. We present a global overview of the whole system. The user can define a biomechanic graphical model to represent the human body in a 3D space, and use tools to perform an automatic or interactive supervised matching between the animated model and the real images to recover the motion. The synthesis part uses the results of matching process to show the motion of the human body that is shown in the real images, from any viewpoint. We use specific criteria to match walking persons from different views. Some results and images are presented.<<ETX>>","PeriodicalId":336218,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115863465","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}
Pub Date : 1994-11-11DOI: 10.1109/MNRAO.1994.346254
M.K. Leung, Herbert Yang
To understand human body motion, one has to be able to identify different body parts. Because of the flexibility of the human body, numerous possible configurations are possible. The paper proposes a novel model based approach to label the outline of a human body. Based on the model, key features of the body can then be identified. In addition, we propose the use of the concept of support, a commonly used notion in dance representation. In our work, a support is defined as the structure on which the body rests. The experimental results of the proposed approach in labeling outlines are very encouraging.<>
{"title":"A model based approach to labelling human body outlines","authors":"M.K. Leung, Herbert Yang","doi":"10.1109/MNRAO.1994.346254","DOIUrl":"https://doi.org/10.1109/MNRAO.1994.346254","url":null,"abstract":"To understand human body motion, one has to be able to identify different body parts. Because of the flexibility of the human body, numerous possible configurations are possible. The paper proposes a novel model based approach to label the outline of a human body. Based on the model, key features of the body can then be identified. In addition, we propose the use of the concept of support, a commonly used notion in dance representation. In our work, a support is defined as the structure on which the body rests. The experimental results of the proposed approach in labeling outlines are very encouraging.<<ETX>>","PeriodicalId":336218,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134481876","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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