With the spread of wearable cameras, many consumer applications ranging from social tagging to video summarization would greatly benefit from people re-identification methods capable of dealing with the egocentric perspective. In this regard, first-person camera views present such a unique setting that traditional re-identification methods results in poor performance when applied to this scenario. In this paper, we present a simple but effective solution that overcomes the limitations of traditional approaches by dividing people images into meaningful body parts. Furthermore, by taking into account human gaze information concerning where people look at when trying to recognize a person, we devise a meaningful way to weight the contributions of different bodyparts. Experimental results validate the proposal on a novel egocentric re-identification dataset, the first of its kind, showing that the performance increases when compared to current state of the art on egocentric sequences is significant.
This paper presents a new approach based on morphological operators for application of biometric identification of individuals by segmentation and analysis of the iris. Algorithms based on morphological operators are developed to segment the iris region from the eye image and also to highlight chosen iris patterns. The extracted features are used to represent and characterize the iris. In order to properly extract the desired patterns, an algorithm is proposed to produce skeletons with unique paths among end-points and nodes. The representation obtained by the morphological processing is stored for identification purposes. To illustrate the efficiency of the morphological approach some results are presented. The proposed system was derived to present low complexity implementation and low storage requirements.
A new approach based on morphological operators is presented for identification of individuals by segmentation and analysis of the iris. Several morphological operators are developed to segment the iris region from the eye image and also to highlight chosen iris pattems. The extracted features are used to represent and uniquely characterize the iris. In order to properly extract the desired pattems. we also propose an algorithm to produce skeletons with unique paths among end-points. This new representation. obtained by the proposed morphological operators is stored for identification purposes. Results are presented to illustrate the efficiency of the identification system. The proposed system was derived to present low complexity implementation and low storage requirements. I. lNTRODUCTIONl h e verification and identification of individuals through biometrics have attracted a lot of attention in the last decade [S.141. As well as others biometrics, the iris has been used in automated recognition systems. and since its characteristics are unique to each individual and stable with age. the m s has a great potentialuse in the biometric noninvasive evaluation [B. 141.The extraction of features can be i q l e m n t e d through several different techniques [ S . 6, 13. 141. However, the choice ol'the feature, as well as of the technique to be used, should take into account the contribution in terms of infomation that can be obtained from it. In other words, the choice of a certain feature depends an its capacity for separating pattems.With this objective. the approach based on nwrphological operafors [I. 2, 4, 7, 12, 131 is used to identify existent pattems in the iris. The basic idea consists of highlighting these pattems, applying a certain sequence of these operators to obtain the stmctures and to arrive into a representation, from where the information will he extracted to characterize them. The proposed representation allows to storage the obtained information in a wmpact and efficient way. while the use of the morphological operators presents advantages U I ternw of low computational wmplmity (processing line) and integration hardware issues. FORMIJLATION OF THE PROBLEMBasically the process of automated iris recognition includes the acquisition of the image. the localization of the rcgion of interest (ROO, the extraction and the matching of pattems [I. 11. 141.During the whole process, several factors can influence in the quality of the image, and consequently. in the decision to he taken, which deternlines if the iris pattem submitted to the system matches or not to a previously stored pattem.Supposing that the acquisition was accomplished in controlled conditions (illumination, distance, framing, etc.), in order to obtain images with the best quality (resolution, clearness and contrast), a pre-processing stage is to he needed. This stage is necessary to enhance certain structures of the iris, to eliminate undesirable effects (e.g., reflections). and still to determine the ROI (located m the portion inside of t...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.