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Locating Human Faces in a Cluttered Scene

A.N. Rajagopalan, K.Sunil Kumar, Jayashree Karlekar, R. Manivasakan, M.Milind Patil, U.B. Desai, P.G. Poonacha, S. Chaudhuri
2000 Graphical Models  
In this paper, we present two new schemes for finding human faces in a photograph. The first scheme adopts a distribution-based model approach to face-finding.  ...  A training data base of face images was constructed in the laboratory.  ...  Finally, the authors thank Nilesh Hiremath for his enthusiastic support in setting up the photo studio and Mohammed Yeasin for several interesting discussions on the face finding problem.  ... 
doi:10.1006/gmod.1999.0511 fatcat:qowd7pqmcjgcvdaaszzdcnrlcq

Layout Estimation of Highly Cluttered Indoor Scenes Using Geometric and Semantic Cues [chapter]

Yu-Wei Chao, Wongun Choi, Caroline Pantofaru, Silvio Savarese
2013 Lecture Notes in Computer Science  
This method fails in highly cluttered scenes in which most of the image features come from clutter instead of the room's geometric structure.  ...  We contribute a new data set of highly cluttered indoor scenes containing people, on which we provide baselines and evaluate our method.  ...  Scene-Human Compatibility Ψ (S, H): This potential measures the likelihood of the human location H = {B, P, T } given the scene hypothesis S.  ... 
doi:10.1007/978-3-642-41184-7_50 fatcat:4qmffp4m2vbovnu2x6xomzdnx4

Action Recognition Robust to Background Clutter by Using Stereo Vision [chapter]

Jordi Sanchez-Riera, Jan Čech, Radu Horaud
2012 Lecture Notes in Computer Science  
The resulting algorithm has a comparable or slightly better recognition accuracy than standard monocular solution in controlled setup with a single actor present in the scene.  ...  However, we show its significantly improved performance in case of strong background clutter due to other people freely moving behind the actor.  ...  In case no face is detected, if the actor turns or the detector miss the face, we simply assume a previous face position. 3.  ... 
doi:10.1007/978-3-642-33863-2_33 fatcat:2vwxs6r2hrgere6a6bqpddjpnu

Individual differences in visual search performance extend from artificial arrays to naturalistic environments [article]

Thomas L. Botch, Brenda D. Garcia, Yeo Bi Choi, Caroline E. Robertson
2021 bioRxiv   pre-print
Visual search is a universal human activity in naturalistic environments.  ...  Traditionally, visual search is investigated under tightly controlled conditions, where head-restricted participants locate a minimalistic target in a cluttered array presented on a computer screen.  ...  Introduction Locating an object in a cluttered environment is a ubiquitous visual behavior.  ... 
doi:10.1101/2021.10.15.464609 fatcat:nuodiio7srasnazmmbedn6vwmm

Partially sparse imaging of stationary indoor scenes

Fauzia Ahmad, Moeness G Amin, Traian Dogaru
2014 EURASIP Journal on Advances in Signal Processing  
In this paper, we exploit the notion of partial sparsity for scene reconstruction associated with through-the-wall radar imaging of stationary targets under reduced data volume.  ...  Partial sparsity implies that the scene being imaged consists of a sparse part and a dense part, with the support of the latter assumed to be known.  ...  Note that an orientation angle of 0°corresponds to the human facing along the positive x direction and the positive angles correspond to a counterclockwise rotation in the horizontal plane.  ... 
doi:10.1186/1687-6180-2014-100 fatcat:2npibota6bhu3gkkacupa44544

There Is a "U" in Clutter: Evidence for Robust Sparse Codes Underlying Clutter Tolerance in Human Vision

P. H. Cox, M. Riesenhuber
2015 Journal of Neuroscience  
The neural mechanisms underlying object recognition in cluttered scenes (i.e., containing more than one object) remain poorly understood.  ...  The ability to recognize objects in clutter is crucial for human vision, yet the underlying neural computations remain poorly understood.  ...  Discussion The feedforward account of rapid object recognition in clutter Numerous studies have shown that humans are able to rapidly and accurately detect objects in cluttered natural scenes containing  ... 
doi:10.1523/jneurosci.1211-15.2015 pmid:26490856 pmcid:PMC4683683 fatcat:dp7knllb7zcvlmkavad47qjzhy

A Goal Oriented Attention Guidance Model [chapter]

Vidhya Navalpakkam, Laurent Itti
2002 Lecture Notes in Computer Science  
In this paper, we propose an architecture to estimate the task-relevance of attended locations in a scene.  ...  Our model guides attention according to a topographic attention guidance map that encodes the bottom-up salience and task-relevance of all locations in the scene.  ...  On a natural cluttered scene, we asked the model to determine the faces of people in the scene and find what they were eating.  ... 
doi:10.1007/3-540-36181-2_45 fatcat:l7picaegp5eafjuuscvzijskp4

The Developing Infant Creates a Curriculum for Statistical Learning

Linda B. Smith, Swapnaa Jayaraman, Elizabeth Clerkin, Chen Yu
2018 Trends in Cognitive Sciences  
From this vantage point, the training sets for statistical learning develop as the infant's sensory-motor abilities develop, yielding a series of ordered data sets for visual learning that differ in content  ...  These changing environments may constitute a developmentally ordered curriculum that optimizes learning across many domains.  ...  Acknowledgments LBS was supported in part by NSF grant BCS-1523982; EMC was supported by NICHD T32HD007475-22, LBS, SW, and CY were supported by Indiana University through the Emerging Area of Research  ... 
doi:10.1016/j.tics.2018.02.004 pmid:29519675 pmcid:PMC5866780 fatcat:2vmlx6eeufdzniph6jlu4cqsom

Symbolic signatures for deformable shapes

S. Ruiz-Correa, L.G. Shapiro, M. Meila, G. Berson, M.L. Cunningham, R.W. Sze
2006 IEEE Transactions on Pattern Analysis and Machine Intelligence  
We demonstrate our system in a series of large-scale experiments that were motivated by specific applications in scene analysis and medical diagnosis.  ...  used to capture the real world only provide a partial view of a scene, so there is partial information pertaining to the objects of interest.  ...  Task 3 (Detection of Human Faces in Complex Scenes) This task considered real range scenes containing human head models and multiple clutter objects.  ... 
doi:10.1109/tpami.2006.23 pmid:16402621 fatcat:7hembfi2kfbdhopuonpnrro6sq

Going beyond vision to improve bionic vision

Wai Ho Li, Titus Jia Jie Tang, Wen Lik Dennis Lui
2013 2013 IEEE International Conference on Image Processing  
Currently, most implanted visual prosthetic systems generate vision by translating sensor data from a headworn camera into electrical stimulation of the human vision system.  ...  This dramatically reduces the usefulness of bionic vision in many real world scenarios. Historically, this problem is treated as immutable pathology.  ...  What if we represent the world symbolically, such as using avatars to represent human faces ( Figure 5 ) to get around the limited resolution in the bionic vision output?  ... 
doi:10.1109/icip.2013.6738320 dblp:conf/icip/LiTL13 fatcat:jhfqfznppvgl3ligwobnv3zye4

Selective visual attention enables learning and recognition of multiple objects in cluttered scenes

Dirk Walther, Ueli Rutishauser, Christof Koch, Pietro Perona
2005 Computer Vision and Image Understanding  
from complex scenes, and that it can strongly improve learning and recognition performance in the presence of large amounts of clutter.  ...  Distinguishing individual objects in a scene would allow unsupervised learning of multiple objects from unlabeled images.  ...  High-resolution background images were provided by TNO Human Factors Research Institute, the Netherlands.  ... 
doi:10.1016/j.cviu.2004.09.004 fatcat:3iyorrhyivhafpl6j3v7tjkuki

Learning an Object Model for Feature Matching in Clutter [chapter]

Toni Tamminen, Jouko Lampinen
2003 Lecture Notes in Computer Science  
We demonstrate how incorporating the shape variation prior into the matching model enhances matching performance in the presence of clutter.  ...  We then estimate the characteristics of the shape variations for a realistic prior on the shapes.  ...  However, when matching faces in cluttered scenes, the performance of the proposed system is clearly superior.  ... 
doi:10.1007/3-540-45103-x_27 fatcat:p4cocdgugzfblh4brtdfipy6li

Wall Clutter Mitigation Using Discrete Prolate Spheroidal Sequences for Sparse Reconstruction of Indoor Stationary Scenes

Fauzia Ahmad, Jiang Qian, Moeness G. Amin
2015 IEEE Transactions on Geoscience and Remote Sensing  
This permits the formation of a linear block sparse model relating the range profile and observation vectors.  ...  Effective wall clutter suppression can then be performed prior to sparse signal image reconstruction.  ...  clutter support to no more than 1.5 m away from the front face of the wall.  ... 
doi:10.1109/tgrs.2014.2345259 fatcat:ldxzylkidbfonjmmaafcgo4pce

Gabor Wavelets and Morphological Shared Weighted Neural Network Based Automatic Face Recognition

Chandrappa D N, Ravishankar M
2013 Signal & Image Processing An International Journal  
Face detection is performed on a cluttered background and crowded scene where a false negative and false positive is detected.  ...  The system is experimented on standard datasets and also on our own dataset of image owing to different illumination conditions and cluttered background in non frontal images with a crowded scene with  ...  Face detection performed on a crowded scene where a false negative and false positive is detected. False positive error includes those locations of face which has been detected as face wrongly.  ... 
doi:10.5121/sipij.2013.4405 fatcat:a6odx65odfg33ltst37u7oiniq

Wall Mitigation Using Discrete Prolate Spheroidal Sequences For Sparse Indoor Image Reconstruction

Fauzia Ahmad, Moeness Amin, Jiang Qian
2013 Zenodo  
Publication in the conference proceedings of EUSIPCO, Marrakech, Morocco, 2013  ...  A simple and effective method for wall clutter mitigation is background subtraction. However, access to empty scene measurements is not available in many applications.  ...  Each face of the dihedral was 0.39 m × 0.28 m. The back and the side walls were covered with RF absorbing material. Measurements from the empty scene without the target were also made.  ... 
doi:10.5281/zenodo.43558 fatcat:x3ve64bvqbcdhky6xhoyasz23y
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