21,424 research outputs found
FARO: FAce Recognition against Occlusions and Expression Variations
Full text linkFARO: FAce Recognition Against Occlusions
and Expression Variations
Maria De Marsico, Member, IEEE, Michele Nappi, and Daniel Riccio
Abstract—Face recognition is widely considered as one of the
most promising biometric techniques, allowing high recognition
rates without being too intrusive. Many approaches have been
presented to solve this special pattern recognition problem, also
addressing the challenging cases of face changes, mainly occurring
in expression, illumination, or pose. On the other hand, less work
can be found in literature that deals with partial occlusions (i.e.,
sunglasses and scarves). This paper presents FAce Recognition
against Occlusions and Expression Variations (FARO) as a new
method based on partitioned iterated function systems (PIFSs),
which is quite robust with respect to expression changes and
partial occlusions. In general, algorithms based on PIFSs compute
a map of self-similarities inside the whole input image, searching
for correspondences among small square regions. However, traditional
algorithms of this kind suffer from local distortions such
as occlusions. To overcome such limitation, information extracted
by PIFS is made local by working independently on each face
component (eyes, nose, and mouth). Distortions introduced by
likely occlusions or expression changes are further reduced by
means of an ad hoc distance measure. In order to experimentally
confirm the robustness of the proposed method to both lighting
and expression variations, as well as to occlusions, FARO has
been tested using AR-Faces database, one of the main benchmarks
for the scientific community in this context. A further validation
of FARO performances is provided by the experimental results
produced on Face Recognition Grand Challenge database
Combining Fractal Coding and Orthogonal Linear Transforms
Full text linkMany desirable properties make fractals a powerful mathematic model applied in several image processing and pattern recognition tasks: image coding, segmentation, feature extraction, and indexing, just to cite some of them. Unfortunately, they are based on a strong asymmetric scheme, consequently suffering from very high coding times. On the other side, linear transforms are quite time balanced, allowing them to be usefully exploited in realtime applications, but they do not provide comparable performances with respect to the image quality for high bit rates. In this paper, we investigate different levels of embedding orthogonal linear transforms in the fractal coding scheme. Experimental results show a clear improved quality for compression ratios up to 15 : 1
Report on Meteorological Research March 1, 1935 (m-1)
No full textThe object of the report was to elucidate in detail the various features of the research program in meteorology being carried on at the Daniel Guggenheim Airship Institute in Akron, Ohio. Mr. L. J. Fangman, of the U.S. Weather Bureau, was collaborating with the author in carrying out work such as a study of autographic records of the various meteorological elements during frontal passages with a view to the possible prediction of the intensity of the accompanying disturbance as it may affect the operation of aircraft and a study of atmospheric gustiness with a view to finding the dependence between frequency end amplitude of velocity fluctuations and the vertical temperature and velocity gradients
(Fourth) Report on Meteorological Activities at the DGAI (8-1-36)(Weather Bureau Copy)
No full textThis report is on the investigations of frontal phenomena at the Daniel Guggenheim Airship Institute in Akron, Ohio from January 1, 1935 through August 1, 1936. The investigation was carried out with the cooperation of the U.S. Bureau of Aeronautics, the U.S. Weather Bureau, the California Institute of Technology, and the Guggenheim Airship Institute. Mr. R.C. Robinson of the Weather Bureau cooperated with the author in carrying out the investigation. The object of the investigation was to determine the intensity of the atmospheric disturbances (i.e. rapidity of wind shift and gustiness) accompanying the passage of cold fronts, along with a study of the characteristics of the air masses involved and other features which might affect the intensity of the disturbance. The report treated thirty cold fronts which passed the station during 1935 to 1936
Archives and Images as Repositories of Time, Language, and Forms from the Past: A Conversation with Daniel Eisenberg
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Robust Face Recognition for Uncontrolled Pose and Illumination Changes
No full textFace recognition has made significant advances in the last decade, but robust commercial applications are still lacking. Current authentication/identification applications are limited to controlled settings, e. g., limited pose and illumination changes, with the user usually aware of being screened and collaborating in the process. Among others, pose and illumination changes are limited. To address challenges from looser restrictions, this paper proposes a novel framework for real-world face recognition in uncontrolled settings named Face Analysis for Commercial Entities (FACE). Its robustness comes from normalization ("correction") strategies to address pose and illumination variations. In addition, two separate image quality indices quantitatively assess pose and illumination changes for each biometric query, before submitting it to the classifier. Samples with poor quality are possibly discarded or undergo a manual classification or, when possible, trigger a new capture. After such filter, template similarity for matching purposes is measured using a localized version of the image correlation index. Finally, FACE adopts reliability indices, which estimate the "acceptability" of the final identification decision made by the classifier. Experimental results show that the accuracy of FACE (in terms of recognition rate) compares favorably, and in some cases by significant margins, against popular face recognition methods. In particular, FACE is compared against SVM, incremental SVM, principal component analysis, incremental LDA, ICA, and hierarchical multiscale local binary pattern. Testing exploits data from different data sets: CelebrityDB, Labeled Faces in the Wild, SCface, and FERET. The face images used present variations in pose, expression, illumination, image quality, and resolution. Our experiments show the benefits of using image quality and reliability indices to enhance overall accuracy, on one side, and to provide for individualized processing of biometric probes for better decision-making purposes, on the other side. Both kinds of indices, owing to the way they are defined, can be easily integrated within different frameworks and off-the-shelf biometric applications for the following: 1) data fusion; 2) online identity management; and 3) interoperability. The results obtained by FACE witness a significant increase in accuracy when compared with the results produced by the other algorithms considered
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