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@TECHREPORT{Atanasoaei_Idiap-RR-43-2010,
                      author = {Atanasoaei, Cosmin and McCool, Chris and Marcel, S{\'{e}}bastien},
                    projects = {Idiap, MOBIO},
                       month = {12},
                       title = {On Improving Face Detection Performance by Modelling Contextual Information},
                        type = {Idiap-RR},
                      number = {Idiap-RR-43-2010},
                        year = {2010},
                 institution = {Idiap},
                    abstract = {In this paper we present a new method to enhance
object detection by removing false alarms and merging multiple
detections in a principled way with few parameters. The method
models the output of an object classi{\"{\i}}¬er which we consider as
the context. A hierarchical model is built using the detection
distribution around a target sub-window to discriminate between
false alarms and true detections. Next the context is used
to iteratively re{\"{\i}}¬ne the detections. Finally the detections are
clustered using the Adaptive Mean Shift algorithm.
The speci{\"{\i}}¬c case of face detection is chosen for this work as
it is a mature {\"{\i}}¬eld of research. We report results that are better
than baseline method on XM2VTS, BANCA and MIT+CMU
face databases. We signi{\"{\i}}¬cantly reduce the number of false
acceptances while keeping the detection rate at approximately
the same level and in certain conditions we recover miss-aligned
detections.},
                         pdf = {https://publications.idiap.ch/attachments/reports/2009/Atanasoaei_Idiap-RR-43-2010.pdf}
}