Journal Publications


  •   S. Biswas, G. Aggarwal and R. Chellappa. Robust Estimation of Albedo for Illumination-invariant Matching and Shape Recovery. Accepted for publication in IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2009. [pdf]

      Abstract In this paper, we propose a non-stationary stochastic filtering framework for the task of albedo estimation from a single image. There are several approaches in literature for albedo estimation, but few include the errors in estimates of surface normals and light source directions to improve the albedo estimate. The proposed approach effectively utilizes the error statistics of surface normals and illumination direction for robust estimation of albedo. The albedo estimate obtained is further used to generate albedo-free normalized images for recovering the shape of an object. Illustrations and experiments are provided to show the efficacy of the approach and its application to illumination-invariant matching and shape recovery.


  •   N. Ramanathan, R. Chellappa and S. Biswas. Age Progression in Human Faces : A Survey. Accepted for publication in Journal of Visual Languages and Computing (Special Issue on Advances in Multimodal Biometric Systems), 2009. [pdf]

      Abstract Facial aging, a new dimension that has recently been added to the problem of face recognition, poses interesting theoretical and practical challenges to the research community. The problem which originally generated interest in the psychophysics and human perception community, has recently found enhanced interest in the computer vision community. How do humans perceive age ? What constitutes an age-invariant signature that can be derived from faces ? How compactly can the facial growth event be described ? How does facial aging impact recognition performance ? In this paper, we give a thorough analysis on the problem of facial aging and further provide a complete account of the many interesting studies that have been performed on this topic from different fields. We offer a comparative analysis of various approaches that have been proposed for problems such as age estimation, appearance prediction, face verification etc. and offer insights into future research on this topic.


  •   S. Biswas, G. Aggarwal and R. Chellappa. An Efficient and Robust Algorithm for Shape Indexing and Retrieval. Under Review in IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)..

      Abstract Most shape matching methods are either fast but too simplistic to give the desired performance or promising as far as performance is concerned but computationally demanding. In this paper, we present a very simple and efficient approach that not only performs almost as good as many state-of-the-art techniques but also scales up to large databases. In the proposed approach, each shape is indexed based on a variety of simple and easily computable features which are invariant to articulations and rigid transformations. The features characterize pairwise geometric relationships between interest points on the shape, thereby providing robustness to the approach. Shapes in the database are ordered according to their similarity with the query shape and similar shapes are retrieved using an efficient scheme which does not involve costly operations like shape-wise alignment or establishing correspondences. Even for a moderate size database of 1000 shapes, the retrieval process is several times faster than most techniques with similar performance. To illustrate the computational and performance advantages of the proposed indexing framework, extensive experiments have been performed on several challenging problems that involve matching shapes. We also highlight the usefulness of the framework to perform robust and efficient shape matching in real images and videos (like figure skating videos) for different applications like human pose estimation and activity classification.


    • Highly Selective Conference Publications


  •   S. Biswas, G. Aggarwal and R. Chellappa. Robust Estimation of Albedo for Illumination-invariant Matching and Shape Recovery. In Proceedings of IEEE International Conference on Computer Vision (ICCV), October, 2007 . [pdf]

      Abstract In this paper, we propose a non-stationary stochastic filtering framework for the task of albedo estimation from a single image. There are several approaches in literature for albedo estimation, but few include the errors in estimates of surface normals and light source directions to improve the albedo estimate. The proposed approach effectively utilizes the error statistics of surface normals and illumination direction for robust estimation of albedo. The albedo estimate obtained is further used to generate albedo-free normalized images for recovering the shape of an object. Illustrations and experiments are provided to show the efficacy of the approach and its application to illumination-invariant matching and shape recovery.


  •   S. Biswas, G. Aggarwal and R. Chellappa. Efficient Indexing for Articulation Invariant Shape Matching and Retrieval. In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), June, 2007 . [pdf]

      Abstract Most shape matching methods are either fast but too simplistic to give the desired performance or promising as far as performance is concerned but computationally demanding. In this paper, we present a very simple and efficient approach that not only performs almost as good as many state-of-the-art techniques but also scales up to large databases. In the proposed approach, each shape is indexed based on a variety of simple and easily computable features which are invariant to articulations and rigid transformations. The features characterize pairwise geometric relationships between interest points on the shape, thereby providing robustness to the approach. Shapes are retrieved using an efficient scheme which does not involve costly operations like shape-wise alignment or establishing correspondences. Even for a moderate size database of 1000 shapes, the retrieval process is several times faster than most techniques with similar performance. Extensive experimental results are presented to illustrate the advantages of our approach as compared to the best in the field.


  •   G. Aggarwal, S. Biswas and R. Chellappa. Symmetric Shapes are Hardly Ambiguous. In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), June, 2007 . [pdf]

      Abstract Given any two images taken under different illumination conditions, there always exist a physically realizable object which is consistent with both the images even if the lighting in each scene is constrained to be a known point light source at infinity. In this paper, we show that images are much less ambiguous for the class of bilaterally symmetric Lambertian objects. In fact, the set of such objects can be partitioned into equivalence classes such that it is always possible to distinguish between two objects belonging to different equivalence classes using just one image per object. The conditions required for two objects to belong to the same equivalence class are very restrictive, thereby leading to the conclusion that images of symmetric objects are hardly ambiguous. The observation leads to an illumination-invariant matching algorithm to compare images of bilaterally symmetric Lambertian objects. Experiments on real data are performed to show the implications of the theoretical result even when the symmetry and Lambertian assumptions are not strictly satisfied.


    • Other Refereed Conference Publications


  •   S. Biswas, G. Aggarwal, N. Ramanathan and R. Chellappa. A Non-generative Approach for Face Recognition Across Aging. IEEE Second International Conference on Biometrics: Theory, Applications and Systems, 2008 . [pdf]

      Abstract Human faces undergo a lot of change in appearance as they age. Though facial aging has been studied for decades, it is only recently that attempts have been made to address the problem from a computational point of view. Most of these early efforts follow a simulation approach in which matching is performed by synthesizing face images at the target age. Given the innumerable different ways in which a face can potentially age, the synthesized aged image may not be similar to the actual aged image. In this paper, we make an attempt to bypass the synthesis step and analyze various aging effects directly from a matching perspective. In particular, we analyze drifts of facial features with aging. Our analysis is based on the observation that facial appearance changes in a coherent manner as people age. We provide measures to capture this coherency in feature drifts. Illustrations and experimental results show the efficacy of such an approach for matching faces across age progression.


  •   S. Biswas , N. K. Ratha, G. Aggarwal and J. Connell. Exploring Ridge Curvature for Fingerprint Indexing. IEEE Second International Conference on Biometrics: Theory, Applications and Systems, 2008 . [pdf]

      Abstract One of the main challenges in building an efficient and scalable automatic fingerprint identification system is to identify features which are highly discriminative and are reproducible across different prints of the same finger. Most existing fingerprint matching approaches rely on minutiae geometry. Relatively, little effort has gone into analyzing ridge flow patterns present in the fingerprint, partly due to difficulty in extracting robust discriminative features from the fingerprint images. In this paper, we analyze the usefulness of ridge curvature information for fingerprint matching and classification applications. Specifically, for an indexing framework, we explore whether the curvature information can be utilized along with the existing minutiae geometry-based features for further reducing the number of potential candidates for fingerprint identification. Experimental results indicate the robustness of the proposed curvature-based characterization and its usefulness in improving the efficiency of existing fingerprint-based identification systems.


  •   M. K. Johnson, D. G. Stork, S. Biswas, Y. Furuichi. Inferring illumination direction estimated from disparate sources in paintings: An investigation into Jan Vermeer's Girl with a pearl earring. SPIE Electronic Imaging: Computer image analysis in the study of art, vol. 6810, 2008 . [pdf]

      Abstract The problem in computer vision of inferring the illumination direction is well studied for digital photographs of natural scenes and recently has become important in the study of realist art as well. We extend previous work on this topic in several ways, testing our methods on Jan Vermeer’s Girl with a pearl earring (c. 1665–1666). We use both model-independent methods (cast-shadow analysis, occluding-contour analysis) and model-based methods (physical models of the pearl, of the girl’s eyes, of her face). Some of these methods provide an estimate of the illuminant position in the three dimensions of the picture space, others in just the two dimensions of the picture plane. Our key contributions are a Bayesian evidence integration scheme for such disparate sources of information and an empirical demonstration of the agreement, or at least consistency, among such estimates in a realist painting. Our methods may be useful to humanist art scholars addressing a number of technical problems in the history of art.


  •   S. Biswas, G. Aggarwal and R. Chellappa. Invariant Geometric Representation of 3D Point Clouds for Registration and Matching. In International Conference on Image Processing (ICIP), October, 2006 . [pdf]

      Abstract Though implicit representations of surfaces have often been used for various computer graphics tasks like modeling and morphing of objects, it has rarely been used for registration and matching of 3D point clouds. Unlike in graphics, where the goal is precise reconstruction, we use isosurfaces to derive a smooth and approximate representation of the underlying point cloud which helps in generalization. Implicit surfaces are generated using a variational interpolation technique. Implicit function values on a set of concentric spheres around the 3D point cloud of object are used as features for matching. Geometric-invariance is achieved by decomposing implicit values based feature set into various spherical harmonics. The decomposition provides a compact representation of 3D point clouds while achieving rotation invariance.


  •   G. Aggarwal, S. Biswas and R. Chellappa. UMD Experiments with FRGC data. In IEEE Workshop on Face Recognition Grand Challenge Experiments (CVPR), June, 2005 . [pdf]

      Abstract Although significant work has been done in the field of face recognition, the performance of state-of-the art face recognition algorithms is not good enough to be effective in operational systems. Though most algorithms work well for controlled images, they are quite susceptible to changes in illumination and pose. Face Recognition Grand Challenge (FRGC) is an effort to examine such issues to suitably guide future research in the area. This paper describes the efforts made at UMD in this direction. We present our results on several experiments suggested in FRGC. We believe that though pattern classification techniques play an extremely significant role in automatic face recognition under controlled conditions, physical modeling is required to generalize across varying situations. Accordingly, we describe a generative approach to recognize faces across varying illumination. Unlike most current methods, our method does not ignore shadows. Instead we use them to our benefit by modeling attached shadows in our formulation.


  •   S. Biswas and K. Nandy. Application of Wavelets in Detection and Classification of Microcalcification in Digital Mammograms - Some Recent Advances. International Conference on Mathematical Biology, 2004 . [pdf]

      Abstract Microcalcification clusters in mammograms are an important early sign of breast cancer. Varying densities of parenchymal tissue make visual detection of these masses very difficult. Computeraided diagnosis using wavelet transform is recently being used to improve the diagnostic accuracy and efficiency of screening mammography. Wavelet coeffcients describe the local geometry of an image in terms of scale and orientation apart from being flexible and robust with respect to image resolution and quality. This paper surveys some recent developments in the application of wavelets in enhancement, detection and classification of microcalcifications in mammograms. Possible areas of future research have also been discussed.



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