FACIAL SOFT BIOMETRICS - Library of Ph.D. Theses | EURASIP

102 8. USER ACCEPTANCE STUDY RELATING TO SOFT BIOMETRICSApplying soft biometrics for person re-identification, with a focus on the frontal vs.side scenarioMotivated by realistic surveillance scenarios, the work addressed the problem of frontal-tosidefacial recognition, providing re–identification algorithms/classifiers that are specifically suitedfor this setting. Emphasis was placed on classifiers that belong in the class of soft biometric traits,specifically color–, texture– and intensity– based traits taken from patches of hair, skin and clothes.Towards providing insight, the work presented different identification experiments that adhere tothe frontal–to–side setting, as well as presented a preliminary analytical study that seeks to impartintuition on the role of the above traits in improving algorithmic reliability. Our analysis describedthe overall error probability, both as a function of collisions and of erroneous categorizations forgiven sizes of authentication groups. In the presence of a moderate reliability of the patches-basedmethod, the analysis suggests promising applications of this method in settings such as pruning ofsearches.Applying soft biometrics quantification and prediction of female facial aestheticsIn terms of female facial aesthetics, we presented a study on facial aesthetics in photographs,where we compared objective measures (namely photograph quality measures, facial beauty characteristicsand non permanent facial features), with human subjective perception. Our analysisrevealed a substantial correlation between different selected traits, and the corresponding MOSrelatedbeauty indices. Specifically we presented that non permanent features can influence highlythe MOS, and based on our analysis we conclude that facial aesthetics in images can indeedbe substantially modifiable. With other words parameters such as the presence of makeup andglasses, the image quality as well as different image post–processing methods can significantlyaffect the resulting MOS. Furthermore we constructed a linear MOS–based metric which wassuccessfully employed to quantify beauty-index variations due to aging and surgery. Our workapplies towards building a basis for designing new image-processing tools that further automateprediction of aesthetics in facial images. Towards this we provided a simulation of an automaticprediction tool based on state-of-art classification algorithms and the designed MOS–predictionmetric.The above approaches were accompanied by a more practically oriented part where we designedan automatic soft biometrics classification tool. Specifically we focused on eye, skin andhair color, as well as on the presence of beard, moustache and glasses.In terms of usability analysis, we presented a user study investigating the preference of a setof test participants on access methods, namely soft biometrics, face, PIN and fingerprint basedaccess methods. This preference was evaluated generally in terms of usability measures, suchas ease of use, intuitiveness and log-in-speed. Furthermore two scenarios were hereby assessed,specifically personal computer access and entrance of a security lab in a crowded environment.The surprising outcome is that although all users were strongly biased towards the PIN basedverification method, by daily use, the biometric based options were overall equally or even significantlybetter rated than the PIN based system. Users appreciated the comfort, easiness and speedof modern technology. Specifically they favored the soft biometrics system, due to the providedprivacy preservation and ease of use.