@conference {12437, title = {Domain adaptation for object recognition: An unsupervised approach}, booktitle = {2011 IEEE International Conference on Computer Vision (ICCV)}, year = {2011}, month = {2011/11/06/13}, pages = {999 - 1006}, publisher = {IEEE}, organization = {IEEE}, abstract = {Adapting the classifier trained on a source domain to recognize instances from a new target domain is an important problem that is receiving recent attention. In this paper, we present one of the first studies on unsupervised domain adaptation in the context of object recognition, where we have labeled data only from the source domain (and therefore do not have correspondences between object categories across domains). Motivated by incremental learning, we create intermediate representations of data between the two domains by viewing the generative subspaces (of same dimension) created from these domains as points on the Grassmann manifold, and sampling points along the geodesic between them to obtain subspaces that provide a meaningful description of the underlying domain shift. We then obtain the projections of labeled source domain data onto these subspaces, from which a discriminative classifier is learnt to classify projected data from the target domain. We discuss extensions of our approach for semi-supervised adaptation, and for cases with multiple source and target domains, and report competitive results on standard datasets.}, keywords = {Data models, data representations, discriminative classifier, Feature extraction, Grassmann manifold, image sampling, incremental learning, labeled source domain, Manifolds, measurement, object category, Object recognition, Principal component analysis, sampling points, semisupervised adaptation, target domain, underlying domain shift, unsupervised approach, unsupervised domain adaptation, Unsupervised learning, vectors}, isbn = {978-1-4577-1101-5}, doi = {10.1109/ICCV.2011.6126344}, author = {Gopalan,R. and Ruonan Li and Chellapa, Rama} } @article {12493, title = {A Learning Approach Towards Detection and Tracking of Lane Markings}, journal = {IEEE Transactions on Intelligent Transportation Systems}, volume = {PP}, year = {2010}, month = {2010/02/17/}, pages = {1 - 12}, abstract = {Road scene analysis is a challenging problem that has applications in autonomous navigation of vehicles. An integral component of this system is the robust detection and tracking of lane markings. It is a hard problem primarily due to large appearance variations in lane markings caused by factors such as occlusion (traffic on the road), shadows (from objects like trees), and changing lighting conditions of the scene (transition from day to night). In this paper, we address these issues through a learning-based approach using visual inputs from a camera mounted in front of a vehicle. We propose the following: 1) a pixel-hierarchy feature descriptor to model the contextual information shared by lane markings with the surrounding road region; 2) a robust boosting algorithm to select relevant contextual features for detecting lane markings; and 3) particle filters to track the lane markings, without knowledge of vehicle speed, by assuming the lane markings to be static through the video sequence and then learning the possible road scene variations from the statistics of tracked model parameters. We investigate the effectiveness of our algorithm on challenging daylight and night-time road video sequences.}, keywords = {Boosting, Context, Context modeling, Feature extraction, lane marking detection, outlier robustness, Roads, tracking and learning, Training, Vehicles}, isbn = {1524-9050}, doi = {10.1109/TITS.2012.2184756}, author = {Gopalan,R. and Hong, T. and Shneier, M. and Chellapa, Rama} } @conference {12490, title = {The role of geometry in age estimation}, booktitle = {2010 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP)}, year = {2010}, month = {2010/03/14/19}, pages = {946 - 949}, publisher = {IEEE}, organization = {IEEE}, abstract = {Understanding and modeling of aging in human faces is an important problem in many real-world applications such as biometrics, authentication, and synthesis. In this paper, we consider the role of geometric attributes of faces, as described by a set of landmark points on the face, in age perception. Towards this end, we show that the space of landmarks can be interpreted as a Grassmann manifold. Then the problem of age estimation is posed as a problem of function estimation on the manifold. The warping of an average face to a given face is quantified as a velocity vector that transforms the average to a given face along a smooth geodesic in unit-time. This deformation is then shown to contain important information about the age of the face. We show in experiments that exploiting geometric cues in a principled manner provides comparable performance to several systems that utilize both geometric and textural cues. We show results on age estimation using the standard FG-Net dataset and a passport dataset which illustrate the effectiveness of the approach.}, keywords = {age estimation, Aging, Biometrics, computational geometry, Face, Face Geometry, Facial animation, Feature extraction, function estimation problem, geometric face attributes, Geometry, Grassmann manifold, human face modeling, human face understanding, HUMANS, Mouth, regression, Regression analysis, SHAPE, Solid modeling, solid modelling, velocity vector}, isbn = {978-1-4244-4295-9}, doi = {10.1109/ICASSP.2010.5495292}, author = {Turaga,P. and Biswas,S. and Chellapa, Rama} } @conference {15060, title = {A New Approach of Dynamic Background Modeling for Surveillance Information}, booktitle = {Computer Science and Software Engineering, 2008 International Conference on}, volume = {1}, year = {2008}, month = {2008/12//}, pages = {850 - 855}, abstract = {This paper presents a new approach of best background modeling for surveillance information. The approach makes orthogonal non-separable wavelet transformation of information frames used for background modeling, extracts the approximate information to reconstruct information frames, filters out the disturbance, shadow and noise from the reconstructed frames, constructs basic background with the method of binary mask images, uses multi-frame combination of non-uniform noise to filter noise in basic background, applies mutual information to detect the situation of adjacent changes. If the background has a gradual change, weighted superposition of multi background modeling images with time will be applied to update the background. If the background has a major or sudden change, the background will remodel from this frame.}, keywords = {approximate information extraction, binary mask images, disturbance filtering, dynamic background modeling, Feature extraction, filtering theory, Image reconstruction, information frame reconstruction, NOISE, noise filtering, orthogonal nonseparable wavelet transformation, Surveillance, surveillance information, Wavelet transforms}, doi = {10.1109/CSSE.2008.601}, author = {Gao,Dongfa and Zhuolin Jiang and Ye,Ming} } @conference {15916, title = {A new multiresolution generalized directional filter bank design and application in image enhancement}, booktitle = {15th IEEE International Conference on Image Processing, 2008. ICIP 2008}, year = {2008}, month = {2008/10//}, pages = {2816 - 2819}, publisher = {IEEE}, organization = {IEEE}, abstract = {In this paper, we present an image enhancement technique based on a new multiscale generalized directional filter bank design. The design presented is a shift-invariant overcomplete representation, which is well suited to extracting geometric features such as edges. Special cases of this design method can be made to reduce to different and improved implementations of the shearlet and the contourlet transforms, which are known to represent certain classes of images optimally. Use of this new filter bank design has proven itself competitive in image restoration for noisy images and is well suited for distinguishing noise from weak edges. Experimental results show that our unique image enhancement technique out-performs wavelet and contourlet based enhancement methods.}, keywords = {Algorithm design and analysis, Approximation error, Channel bank filters, contourlet transform, Design methodology, Discrete transforms, Feature extraction, Filter bank, Frequency, geometric feature extraction, Image Enhancement, IMAGE PROCESSING, image resolution, image restoration, Multidimensional digital filters, Multidimensional systems, multiresolution generalized directional filter bank design, shearlet transform, shift-invariant overcomplete representation, transforms, Wavelet transforms}, isbn = {978-1-4244-1765-0}, doi = {10.1109/ICIP.2008.4712380}, author = {Patel, Vishal M. and Easley,G. R and Healy,D. M} } @article {14506, title = {Statistical Relational Learning as an Enabling Technology for Data Acquisition and Data Fusion in Heterogeneous Sensor Networks}, year = {2008}, month = {2008/06/29/}, institution = {OFFICE OF RESEARCH ADMINISTRATION AND ADVANCEMENT, UNIVERSITY OF MARYLAND COLLEGE PARK}, abstract = {Our work has focused on developing new cost sensitive feature acquisition and classification algorithms, mapping these algorithms onto camera networks, and creating a test bed of video data and implemented vision algorithms that we can use to implement these. First, we will describe a new algorithm that we have developed for feature acquisition in Hidden Markov Models (HMMs). This is particularly useful for inference tasks involving video from a single camera, in which the relationship between frames of video can be modeled as a Markov chain. We describe this algorithm in the context of using background subtraction results to identify portions of video that contain a moving object. Next, we will describe new algorithms that apply to general graphical models. These can be tested using existing test sets that are drawn from a range of domains in addition to sensor networks.}, keywords = {*ALGORITHMS, *CLASSIFICATION, data acquisition, DATA FUSION, Detectors, Feature extraction, HMM(HIDDEN MARKOV MODELS), NETWORKS, NUMERICAL MATHEMATICS, PE611102, RANDOM FIELDS, STATISTICS AND PROBABILITY, TEST SETS, VIDEO SIGNALS}, url = {http://stinet.dtic.mil/oai/oai?\&verb=getRecord\&metadataPrefix=html\&identifier=ADA500520}, author = {Jacobs, David W. and Getoor, Lise} } @conference {13849, title = {Reranking for Sentence Boundary Detection in Conversational Speech}, booktitle = {2006 IEEE International Conference on Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings}, volume = {1}, year = {2006}, month = {2006/05/14/19}, pages = {I-I - I-I}, publisher = {IEEE}, organization = {IEEE}, abstract = {We present a reranking approach to sentence-like unit (SU) boundary detection, one of the EARS metadata extraction tasks. Techniques for generating relatively small n-best lists with high oracle accuracy are presented. For each candidate, features are derived from a range of information sources, including the output of a number of parsers. Our approach yields significant improvements over the best performing system from the NIST RT-04F community evaluation}, keywords = {Automatic speech recognition, conversational speech, data mining, Ear, EARS metadata extraction tasks, Feature extraction, hidden Markov models, meta data, Model driven engineering, NIST, NIST RT-04F community evaluation, oracle accuracy, performance evaluation, reranking, sentence-like unit boundary detection, Speech processing, Speech recognition, Telephony}, isbn = {1-4244-0469-X}, doi = {10.1109/ICASSP.2006.1660078}, author = {Roark,B. and Liu,Yang and Harper,M. and Stewart,R. and Lease,M. and Snover,M. and Shafran,I. and Dorr, Bonnie J and Hale,J. and Krasnyanskaya,A. and Yung,L.} } @conference {18327, title = {Detection, analysis and matching of hair}, booktitle = {Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on}, volume = {1}, year = {2005}, month = {2005/10//}, pages = {741 - 748 Vol. 1 - 741 - 748 Vol. 1}, abstract = {We develop computational models for measuring hair appearance for comparing different people. The models and methods developed have applications to person recognition and face image indexing. An automatic hair detection algorithm is described and results reported. A multidimensional representation of hair appearance is presented and computational algorithms are described. Results on a dataset of 524 subjects are reported. Identification of people using hair attributes is compared to eigenface-based recognition along with a joint, eigenface-hair based identification.}, keywords = {automatic hair detection, eigenface-based recognition, eigenface-hair based identification, Eigenvalues and eigenfunctions, face image indexing, face recognition, Feature extraction, hair analysis, hair appearance, hair attributes, hair matching, Image matching, image representation, multidimensional representation, person recognition}, doi = {10.1109/ICCV.2005.75}, author = {Yacoob,Yaser and Davis, Larry S.} } @article {18462, title = {Processing of reverberant speech for time-delay estimation}, journal = {IEEE Transactions on Speech and Audio Processing}, volume = {13}, year = {2005}, month = {2005/11//}, pages = {1110 - 1118}, abstract = {In this paper, we present a method of extracting the time-delay between speech signals collected at two microphone locations. Time-delay estimation from microphone outputs is the first step for many sound localization algorithms, and also for enhancement of speech. For time-delay estimation, speech signals are normally processed using short-time spectral information (either magnitude or phase or both). The spectral features are affected by degradations in speech caused by noise and reverberation. Features corresponding to the excitation source of the speech production mechanism are robust to such degradations. We show that these source features can be extracted reliably from the speech signal. The time-delay estimate can be obtained using the features extracted even from short segments (50-100 ms) of speech from a pair of microphones. The proposed method for time-delay estimation is found to perform better than the generalized cross-correlation (GCC) approach. A method for enhancement of speech is also proposed using the knowledge of the time-delay and the information of the excitation source.}, keywords = {Acoustic noise, acoustic signal processing, array signal processing, data mining, Degradation, delay estimation, Feature extraction, Hilbert envelope, localization algorithm, microphone arrays, microphone location, Microphones, Phase estimation, reverberation, short-time spectral information, Signal processing, source features, source information excitation, speech enhancement, Speech processing, speech production mechanism, speech signal, time-delay, time-delay estimation}, isbn = {1063-6676}, doi = {10.1109/TSA.2005.853005}, author = {Yegnanarayana,B. and Prasanna,S. R.M and Duraiswami, Ramani and Zotkin,Dmitry N} } @conference {16944, title = {A Rank-by-Feature Framework for Unsupervised Multidimensional Data Exploration Using Low Dimensional Projections}, booktitle = {IEEE Symposium on Information Visualization, 2004. INFOVIS 2004}, year = {2004}, month = {2004///}, pages = {65 - 72}, publisher = {IEEE}, organization = {IEEE}, abstract = {Exploratory analysis of multidimensional data sets is challenging because of the difficulty in comprehending more than three dimensions. Two fundamental statistical principles for the exploratory analysis are (1) to examine each dimension first and then find relationships among dimensions, and (2) to try graphical displays first and then find numerical summaries (D.S. Moore, (1999). We implement these principles in a novel conceptual framework called the rank-by-feature framework. In the framework, users can choose a ranking criterion interesting to them and sort 1D or 2D axis-parallel projections according to the criterion. We introduce the rank-by-feature prism that is a color-coded lower-triangular matrix that guides users to desired features. Statistical graphs (histogram, boxplot, and scatterplot) and information visualization techniques (overview, coordination, and dynamic query) are combined to help users effectively traverse 1D and 2D axis-parallel projections, and finally to help them interactively find interesting features}, keywords = {axis-parallel projections, boxplot, color-coded lower-triangular matrix, computational complexity, computational geometry, Computer displays, Computer science, Computer vision, Data analysis, data mining, data visualisation, Data visualization, Displays, dynamic query, Educational institutions, exploratory data analysis, feature detection, feature detection/selection, Feature extraction, feature selection, graph theory, graphical displays, histogram, Information Visualization, interactive systems, Laboratories, Multidimensional systems, Principal component analysis, rank-by-feature prism, scatterplot, statistical analysis, statistical graphics, statistical graphs, unsupervised multidimensional data exploration, very large databases}, isbn = {0-7803-8779-3}, doi = {10.1109/INFVIS.2004.3}, author = {Seo,J. and Shneiderman, Ben} } @conference {11894, title = {Hidden Markov models for silhouette classification}, booktitle = {Automation Congress, 2002 Proceedings of the 5th Biannual World}, volume = {13}, year = {2002}, month = {2002///}, pages = {395 - 402}, publisher = {IEEE}, organization = {IEEE}, abstract = {In this paper, a new technique for object classification from silhouettes is presented. Hidden Markov models are used as a classification mechanism. Through a set of experiments, we show the validity of our approach and show its invariance under severe rotation conditions. Also, a comparison with other techniques that use hidden Markov models for object classification from silhouettes is presented.}, keywords = {Computer vision, Feature extraction, Fourier transforms, hidden Markov models, HMM, image classification, Neural networks, object classification, Object recognition, parameter estimation, pattern recognition, Probability distribution, Shape measurement, silhouette classification, Wavelet transforms}, isbn = {1-889335-18-5}, doi = {10.1109/WAC.2002.1049575}, author = {Abd-Almageed, Wael and Smith,C.} } @conference {15592, title = {Robust matching of wavelet features for sub-pixel registration of Landsat data}, booktitle = {Geoscience and Remote Sensing Symposium, 2001. IGARSS {\textquoteright}01. IEEE 2001 International}, volume = {2}, year = {2001}, month = {2001///}, pages = {706 -708 vol.2 - 706 -708 vol.2}, abstract = {For many Earth and space science applications, automatic geo-registration at sub-pixel accuracy has become a necessity. In this work, we are focusing on building an operational system, which will provide a sub-pixel accuracy registration of Landsat-5 and Landsat-7 data. The input to our registration method consists of scenes that have been geometrically and radiometrically corrected. Such preprocessed scenes are then geo-registered relative to a database of Landsat chips. The method assumes a transformation composed of a rotation and a translation, and utilizes rotation- and translation-invariant wavelets to extract image features that are matched using statistically robust feature matching and a partial Hausdorff distance metric. The registration process is described and results on four Landsat input scenes of the Washington, D.C., area are presented}, keywords = {Feature extraction, geo-registration, geophysical measurement technique, geophysical signal processing, geophysical techniques, Hausdorff distance metric, image registration, infrared, IR, land surface, Landsat, Landsat-5, Landsat-7, multispectral remote sensing, robust feature matching, robust matching, sub pixel registration, subpixel accuracy, terrain mapping, visible, wavelet feature, wavelet method, Wavelet transforms}, doi = {10.1109/IGARSS.2001.976609}, author = {Le Moigne,J. and Netanyahu,N. S and Masek,J. G and Mount, Dave and Goward, S.N.} } @conference {15591, title = {Geo-registration of Landsat data by robust matching of wavelet features}, booktitle = {Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International}, volume = {4}, year = {2000}, month = {2000///}, pages = {1610 -1612 vol.4 - 1610 -1612 vol.4}, abstract = {The goal of our project is to build an operational system, which will provide a sub-pixel accuracy registration of Landsat-5 and Landsat-7 data. Integrated within an automated mass processing/analysis system for Landsat data (REALM), the input to our registration method consists of scenes that have been geometrically and radiometrically corrected, as well as pre-processed for the detection of clouds and cloud shadows. Such pre-processed scenes are then geo-registered relative to a database of Landsat chips. This paper describes our registration process, including the use of a database of landmark chips, a feature extraction performed by an overcomplete wavelet representation, and feature matching using statistically robust techniques. Knowing the approximate longitudes and latitudes of the four corners of the scene, a subset of chips which represent landmarks included in the scene are extracted from the database. For each of these selected landmark chips, a corresponding window is extracted from the scene, and each chip-window pair is registered using our robust wavelet feature matching. First results and future directions are presented in the paper}, keywords = {atmospheric techniques, automated mass processing/analysis system, chip-window pair, cloud shadows, Clouds, Feature extraction, feature matching, geo-registration, geometrically corrected scene, geophysical signal processing, Image matching, image registration, landmark chips, Landsat chips, Landsat data, Landsat-5 data, Landsat-7 data, overcomplete wavelet representation, pre-processed scenes, radiometrically corrected scene, REALM, Remote sensing, robust matching, robust wavelet feature matching, scenes, statistically robust techniques, sub-pixel accuracy registration, wavelet features, Wavelet transforms, window}, doi = {10.1109/IGARSS.2000.857287}, author = {Le Moigne,J. and Netanyahu,N. S and Masek,J. G and Mount, Dave and Goward,S. and Honzak,M.} } @conference {18322, title = {Computing 3-D head orientation from a monocular image sequence}, booktitle = {Automatic Face and Gesture Recognition, 1996., Proceedings of the Second International Conference on}, year = {1996}, month = {1996/10//}, pages = {242 - 247}, abstract = {An approach for estimating 3D head orientation in a monocular image sequence is proposed. The approach employs recently developed image-based parameterized tracking for face and face features to locate the area in which a sub-pixel parameterized shape estimation of the eye{\textquoteright}s boundary is performed. This involves tracking of five points (four at the eye corners and the fifth is the lip of the nose). The authors describe an approach that relies on the coarse structure of the face to compute orientation relative to the camera plane. Our approach employs projective invariance of the cross-ratios of the eye corners and anthropometric statistics to estimate the head yaw, roll and pitch. Analytical and experimental results are reported}, keywords = {3D head orientation computation, anthropometric statistics, camera plane, coarse structure, eye, eye boundary, eye corners, face features, face recognition, Feature extraction, head pitch, head roll, head yaw, Image sequences, image-based parameterized tracking, monocular image sequence, projective cross-ratio invariance, sub-pixel parameterized shape estimation, tracking}, doi = {10.1109/AFGR.1996.557271}, author = {Horprasert,T. and Yacoob,Yaser and Davis, Larry S.} } @article {16656, title = {Feature discovery and classification of Doppler umbilical artery blood flow velocity waveforms}, journal = {Computers in Biology and Medicine}, volume = {26}, year = {1996}, month = {1996/11//}, pages = {451 - 462}, abstract = {Doppler umbilical artery blood flow velocity waveform measurements are used in perinatal surveillance for the evaluation of fetal condition. There is an ongoing debate on the predictive value of Doppler measurements concerning the critical effect of the selection of parameters for the interpretation of Doppler waveforms. In this paper, we describe how neural network methods can be used both to discover relevant classification features and subsequently to classify Doppler umbilical artery blood flow velocity waveforms. Results obtained from 199 normal and high risk patients{\textquoteright} umbilical artery waveforms highlighted a classification concordance varying from 90 to 98\% accuracy.}, keywords = {Doppler umbilical artery blood flow velocity waveforms, Feature extraction, IMAGE PROCESSING, Pattern classification}, isbn = {0010-4825}, doi = {10.1016/S0010-4825(96)00018-2}, url = {http://www.sciencedirect.com/science/article/pii/S0010482596000182}, author = {Baykal,Nazife and Reogia,James A. and Yalabik,Nese and Erkmen,Aydan and Beksac,M.Sinan} } @mastersthesis {18816, title = {Automated Manufacturability Analysis of Machined Parts}, year = {1995}, month = {1995///}, school = {UNIVERSITY OF MARYLAND, COLLEGE PARK}, abstract = {Because of pressing demands to reduce lead time and product cost, increasing research attention is being given to integration of engineering design and manufacturing. In this thesis, a systematic approach has been developed for computer-aided manufacturability analysis of machined parts. This approach can be used during design stages to improve the product quality from the manufacturing point of view.

Evaluating the manufacturability of a proposed design involves determining whether or not it is manufacturable with a given set of manufacturing operations - and if so, then finding the associated manufacturing efficiency. In this research, the design is represented as a solid model. The tolerance and surface finish information is represented as attributes of various faces of the solid model. Machining features are used to model the available machining operations Since there can be several different ways to manufacture a proposed design, this requires considering alternative ways to manufacture it, in order to determine which one best meets the design and manufacturing objectives.

The approach developed in this thesis is based on the systematic exploration of various machining plans. The first step is to identify all machining features which can potentially be used to machine the given design. Using these features, different machining plans are generated. Each time a new plan generated, it is examined to find whether it can produce the desired design tolerances. If a plan is found to be capable of meeting the tolerance specifications, then its rating is computed. If no machining plan can be found that is capable of producing the design, then the design cannot be machined using the given set of machining operations; otherwise, the manufacturability rating of the design is computed. Since various alternative ways of machining the part are considered in this approach, the conclusions about the manufacturability are more realistic compared to the approach where just one alternative is considered.

It is anticipated that this research will help in speeding up the evaluation of new product designs in order to decide how or whether to manufacture them. Such a capability will be useful in responding quickly to changing demands and opportunities in the marketplace.}, keywords = {Automation, computer aided manufacturing, computer integrated manufacturing, Feature extraction, flexible manufacturing, manufacturability, Manufacturing, Solid modeling}, url = {http://drum.lib.umd.edu//handle/1903/5693}, author = {Gupta, Satyandra K.} } @article {18833, title = {Feature Recognition for Manufacturability Analysis}, volume = {ISR; TR 1994-10}, year = {1994}, month = {1994///}, institution = {Institute for Systems Research, University of Maryland, College Park}, abstract = {While automated recognition of features has been attempted for a wide range of applications, no single existing approach possesses the functionality required to perform manufacturability analysis. In this paper, we present a methodology for taking a CAD model and extracting a set of machinable features suitable for generating all alternative interpretations of the model as collections of MRSEVs (Material Removal Shape Element Volumes, a STEP-based library of machining, features). This set of MRSEVs is to be employed for manufacturability analysis. The algorithm handles a variety of features including those describing holes, pockets, slots, and chamfering and filleting operations. In addition, it considers elementary accessibility constraints for these features and is provably complete over a, significant class of machinable parts the features describe. Further, the approach has low-order polynomial-time worst-case complexity.}, keywords = {algorithms, Automation, COMPUTER AIDED DESIGN, computer aided manufacturing, computer integrated manufacturing, Feature extraction, manufacturability, Manufacturing, Solid modeling, Systems Integration}, url = {http://drum.lib.umd.edu//handle/1903/5490}, author = {Regli,W. C. and Gupta, Satyandra K. and Nau, Dana S.} } @article {18809, title = {A Systematic Approach for Analyzing the Manufacturability of Machined Parts}, volume = {ISR; TR 1993-76}, year = {1993}, month = {1993///}, institution = {Institute for Systems Research, University of Maryland, College Park}, abstract = {The ability to quickly introduce new quality products is a decisive factor in capturing market share. Because of pressing demands to reduce lead time, analyzing the manufacturability of the proposed design has become an important step in the design stage. This paper presents an approach for analyzing the manufacturability of machined parts.

Evaluating the manufacturability of a proposed design involves determining whether or not it is manufacturable with a given set of manufacturing operations - and if so, then finding the associated manufacturing efficiency. Since there can be several different ways to manufacture a proposed design, this requires us to consider different ways to manufacture it, in order to determine which one best meets the design and manufacturing objectives.

The first step in our approach is to identify all machining operations which can potentially be used to create the given design. Using these operations, we generate different operation plans for machining the part. Each time we generate a new operation plan, we examine whether it can produce the desired shape and tolerances, and calculate its manufacturability rating. If no operation plan can be found that is capable of producing the design, then the given design is considered unmachinable; otherwise, the manufacturability rating for the design is the rating of the best operation plan.

We anticipate that by providing feedback about possible problems with the design, this work will help in speeding up the evaluation of new product designs in order to decide how or whether to manufacture them. Such a capability will be useful in responding quickly to changing demands and opportunities in the marketplace.}, keywords = {Automation, computer aided manufacturing, Feature extraction, manufacturability, Systems Integration}, url = {http://drum.lib.umd.edu//handle/1903/5420}, author = {Gupta, Satyandra K. and Nau, Dana S.} } @article {18840, title = {Generation and Evaluation of Alternative Operation}, volume = {ISR; TR 1992-20}, year = {1992}, month = {1992///}, institution = {Institute for Systems Research, University of Maryland, College Park}, abstract = {This paper presents a new and systematic approach to assist decision-making in selecting machining operation sequences. The approach is to produce alternative interpretations of design as different collections of machinable features, use these interpretations to generate alternative machining operation sequences, and evaluate the cost and achievable machining accuracy of each operations sequence. Given the operation sequences and their evaluations, it is then possible to calculate the performance measures of interest, and use these performance measures to select, from among the various alternatives, one or more of them that can best balance the need for a quality product against the need for efficient machining.}, keywords = {Automation, computer aided manufacturing, computer integrated manufacturing, Feature extraction, flexible manufacturing, Manufacturing, Manufacturing Systems, Solid modeling}, url = {http://drum.lib.umd.edu//handle/1903/5203}, author = {Nau, Dana S. and Zhang,G. M. and Gupta, Satyandra K.} } @conference {14169, title = {Hierarchical curve representation}, booktitle = {, 11th IAPR International Conference on Pattern Recognition, 1992. Vol.III. Conference C: Image, Speech and Signal Analysis, Proceedings}, year = {1992}, month = {1992/09/30/Aug-3}, pages = {143 - 146}, publisher = {IEEE}, organization = {IEEE}, abstract = {Presents a robust method for describing planar curves in multiple resolution using curvature information. The method is developed by taking into account the discrete nature of digital images as well as the discrete aspect of a multiresolution structure (pyramid). The authors deal with the robustness of the technique, which is due to the additional information that is extracted from observing the behavior of corners in the pyramid. Furthermore the resulting algorithm is conceptually simple and easily parallelizable. They develop theoretical results, analyzing the curvature of continuous curves in scale-space, which show the behavior of curvature extrema under varying scale. These results are used to eliminate any ambiguities that might arise from sampling problems due to the discreteness of the representation. Finally, experimental results demonstrate the potential of the method}, keywords = {Automation, continuous curves, curvature, data mining, digital images, Educational institutions, Feature extraction, hierarchical curve representation, IMAGE PROCESSING, image recognition, image resolution, Image segmentation, multiresolution structure, Object recognition, planar curves, pyramid, Robustness, Sampling methods, Smoothing methods}, isbn = {0-8186-2920-7}, doi = {10.1109/ICPR.1992.201947}, author = {Ferm{\"u}ller, Cornelia and Kropatsch,W.} } @conference {14233, title = {Multi-resolution shape description by corners}, booktitle = {, 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1992. Proceedings CVPR {\textquoteright}92}, year = {1992}, month = {1992/06/15/18}, pages = {271 - 276}, publisher = {IEEE}, organization = {IEEE}, abstract = {A robust method for describing planar curves in multiple resolution using curvature information is presented. The method is developed by taking into account the discrete nature of digital images as well as the discrete aspect of a multiresolution structure (pyramid). The main contribution lies in the robustness of the technique, which is due to the additional information that is extracted from observing the behavior of corners in the whole pyramid. Furthermore, the resulting algorithm is conceptually simple and easily parallelizable. Theoretical results are developed analyzing the curvature of continuous curves in scale-space and showing the behavior of curvature extrema under varying scale. The results are used to eliminate any ambiguities that might arise from sampling problems due to the discreteness of the representation. Experimental results demonstrate the potential of the method}, keywords = {ambiguities, Automation, computational geometry, Computer vision, continuous curves, corners, curvature extrema, curvature information, curve fitting, digital images, Feature extraction, IMAGE PROCESSING, image resolution, Image segmentation, Laboratories, multiple resolution, multiresolution structure, parallelizable, planar curves, Robustness, Sampling methods, scale-space, SHAPE, Smoothing methods, varying scale}, isbn = {0-8186-2855-3}, doi = {10.1109/CVPR.1992.223264}, author = {Ferm{\"u}ller, Cornelia and Kropatsch,W.} }