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Browsing CBCL Memos (1993 - 2004) by Title

Research and Teaching Output of the MIT Community

Browsing CBCL Memos (1993 - 2004) by Title

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  • Jarudi, Izzat N.; Sinha, Pawan (2003-03-01)
    The central challenge in face recognition lies in understanding the role different facial features play in our judgments of identity. Notable in this regard are the relative contributions of the internal (eyes, nose and ...
  • Rakhlin, Alexander; Panchenko, Dmitry; Mukherjee, Sayan (2004-01-27)
    In this paper we focus on the problem of estimating a bounded density using a finite combination of densities from a given class. We consider the Maximum Likelihood Procedure (MLE) and the greedy procedure described by ...
  • Yip, Andrew; Sinha, Pawan (2001-12-13)
    One of the key challenges in face perception lies in determining the contribution of different cues to face identification. In this study, we focus on the role of color cues. Although color appears to be a salient attribute ...
  • Sinha, Pawan; Torralba, Antonio (2001-08-01)
    Brightness judgments are a key part of the primate brain's visual analysis of the environment. There is general consensus that the perceived brightness of an image region is based not only on its actual luminance, but also ...
  • Yokono, Jerry Jun; Poggio, Tomaso (2004-04-27)
    Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. Such a descriptor--based on a set of ...
  • Ho, Purdy (2001-05-31)
    In this report, a face recognition system that is capable of detecting and recognizing frontal and rotated faces was developed. Two face recognition methods focusing on the aspect of pose invariance are presented and ...
  • Wolf, Lior; Amnon Shashua,; Mukherjee, Sayan (2004-01-27)
    Array technologies have made it possible to record simultaneously the expression pattern of thousands of genes. A fundamental problem in the analysis of gene expression data is the identification of highly relevant genes ...
  • Niyogi, Partha (1995-05-12)
    In most classical frameworks for learning from examples, it is assumed that examples are randomly drawn and presented to the learner. In this paper, we consider the possibility of a more active learner who is allowed ...
  • Weiss, Yar; Adelson, Edward H. (1998-02-01)
    In order to estimate the motion of an object, the visual system needs to combine multiple local measurements, each of which carries some degree of ambiguity. We present a model of motion perception whereby measurements ...
  • Papgeorgiou, Constantine P.; Girosi, Federico; Poggio, Tomaso (1998-05-01)
    This paper presents a new paradigm for signal reconstruction and superresolution, Correlation Kernel Analysis (CKA), that is based on the selection of a sparse set of bases from a large dictionary of class- specific basis ...
  • Evgeniou, Theodoros; Poggio, Tomaso (1997-09-01)
    We discuss the problem of finding sparse representations of a class of signals. We formalize the problem and prove it is NP-complete both in the case of a single signal and that of multiple ones. Next we develop a simple ...
  • Mukherjee, Sayan; Niyogi, Partha; Poggio, Tomaso; Rifkin, Ryan (2002-12-01)
    Solutions of learning problems by Empirical Risk Minimization (ERM) need to be consistent, so that they may be predictive. They also need to be well-posed, so that they can be used robustly. We show that a statistical ...
  • Hofmann, Thomas; Puzicha, Jan (1998-02-01)
    Modeling and predicting co-occurrences of events is a fundamental problem of unsupervised learning. In this contribution we develop a statistical framework for analyzing co-occurrence data in a general setting where ...
  • Knoblich, Ulf; Riesenhuber, Maximilan (2002-03-15)
    Tsunoda et al. (2001) recently studied the nature of object representation in monkey inferotemporal cortex using a combination of optical imaging and extracellular recordings. In particular, they examined IT neuron ...
  • Osuna, Edgar; Freund, Robert; Girosi, Federico (1997-03-01)
    The Support Vector Machine (SVM) is a new and very promising classification technique developed by Vapnik and his group at AT&T Bell Labs. This new learning algorithm can be seen as an alternative training technique ...
  • Shelton, Christian R. (1998-12-01)
    This paper describes the problem of three-dimensional object correspondence and presents an algorithm for matching two three-dimensional colored surfaces using polygon reduction and the minimization of an energy function. ...
  • Kumar, Vinay P. (2002-09-01)
    This thesis proposes a methodology for the design of man-machine interfaces by combining top-down and bottom-up processes in vision. From a computational perspective, we propose that the scientific-cognitive question ...
  • Papageorgiou, Constantine P.; Poggio, Tomaso (1999-10-13)
    This paper describes a general, trainable architecture for object detection that has previously been applied to face and peoplesdetection with a new application to car detection in static images. Our technique is a ...
  • Papageorgiou, Constantine P. (2000-05-01)
    This thesis presents a general, trainable system for object detection in static images and video sequences. The core system finds a certain class of objects in static images of completely unconstrained, cluttered scenes ...
  • Dill, Marcus; Edelman, Shimon (1997-06-01)
    Human object recognition is generally considered to tolerate changes of the stimulus position in the visual field. A number of recent studies, however, have cast doubt on the completeness of translation invariance. In a ...
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