2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)最新文献_第2页

Ear recognition after ear lobe surgery: A preliminary study 耳垂手术后的耳识别:初步研究

2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA) Pub Date : 2016-02-01 DOI: 10.1109/ISBA.2016.7477249

Ramachandra Raghavendra, K. Raja, C. Busch

{"title":"Ear recognition after ear lobe surgery: A preliminary study","authors":"Ramachandra Raghavendra, K. Raja, C. Busch","doi":"10.1109/ISBA.2016.7477249","DOIUrl":"https://doi.org/10.1109/ISBA.2016.7477249","url":null,"abstract":"Earlobe surgeries are performed with the intention to correct the ear characteristics both locally and globally and also to beautify the appearance. Since performing the surgery (both for beautification and corrections) will alter the original ear features to the greater extent thereby poses a significant challenge for ear recognition. In this work, we introduce and explore this problem of ear recognition after ear lobe surgery. To this extent, we prepared a new ear surgery database comprising of 50 subjects with both pre and post surgery ear samples. We then propose a new scheme for ear recognition based on the hybrid fusion of block features extracted from the ear images using Histogram of Oriented Gradients (HoG) and Local Phase Quantisation (LPQ). We present extensive experiments on the ear surgery database by comparing the performance of eight different state-of-the-art schemes to study the effect of ear surgeries on ear recognition accuracy. The results on the ear surgery database indicate a great challenge as the eight different state-of-the-art schemes are unable to provide acceptable levels of identification performance.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129841530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Spotting fingerspelled words from sign language video by temporally regularized canonical component analysis 基于时间正则化正则分量分析的手势语视频手势语识别方法

2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA) Pub Date : 2016-02-01 DOI: 10.1109/ISBA.2016.7477238

Shohei Tanaka, A. Okazaki, N. Kato, H. Hino, K. Fukui

{"title":"Spotting fingerspelled words from sign language video by temporally regularized canonical component analysis","authors":"Shohei Tanaka, A. Okazaki, N. Kato, H. Hino, K. Fukui","doi":"10.1109/ISBA.2016.7477238","DOIUrl":"https://doi.org/10.1109/ISBA.2016.7477238","url":null,"abstract":"A method for spotting specific words in sign language video is proposed. In classes and talks given using Japanese Sign Language, words that do not have a defined sign, such as the names of people, objects, and places, are represented by sets of multiple characters from the Japanese finger alphabet. The difficulty of recognizing these words has created strong demand for the ability to spot specific words in order to help interpreters and the audience to follow a talk. We address the spotting task by employing the basic idea of temporal regularized canonical correlation analysis (TRCCA), which can simultaneously handle shape and motion information about a 3D object. The classification accuracy of TRCCA is enhanced by incorporating two functions: 1) parallel processing with multiple time scales, 2) strong implicit feature mapping by nonlinear orthogonalization. The enhanced TRCCA is called \"kernel orthogonal TRCCA (KOTRCCA)\". The effectiveness of the proposed method using KOTRCCA is demonstrated through experiments spotting eight different words in sign language videos.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122470982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Determining the best attributes for surveillance video keywords generation 确定监控视频关键字生成的最佳属性

2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA) Pub Date : 2016-02-01 DOI: 10.1109/ISBA.2016.7477239

Liangchen Liu, A. Wiliem, Shaokang Chen, Kun Zhao, B. Lovell

{"title":"Determining the best attributes for surveillance video keywords generation","authors":"Liangchen Liu, A. Wiliem, Shaokang Chen, Kun Zhao, B. Lovell","doi":"10.1109/ISBA.2016.7477239","DOIUrl":"https://doi.org/10.1109/ISBA.2016.7477239","url":null,"abstract":"Automatic video keyword generation is one of the key ingredients in reducing the burden of security officers in analyzing surveillance videos. Keywords or attributes are generally chosen manually based on expert knowledge of surveillance. Most existing works primarily aim at either supervised learning approaches relying on extensive manual labelling or hierarchical probabilistic models that assume the features are extracted using the bag-of-words approach; thus limiting the utilization of the other features. To address this, we turn our attention to automatic attribute discovery approaches. However, it is not clear which automatic discovery approach can discover the most meaningful attributes. Furthermore, little research has been done on how to compare and choose the best automatic attribute discovery methods. In this paper, we propose a novel approach, based on the shared structure exhibited amongst meaningful attributes, that enables us to compare between different automatic attribute discovery approaches. We then validate our approach by comparing various attribute discovery methods such as PiCoDeS on two attribute datasets. The evaluation shows that our approach is able to select the automatic discovery approach that discovers the most meaningful attributes. We then employ the best discovery approach to generate keywords for videos recorded from a surveillance system. This work shows it is possible to massively reduce the amount of manual work in generating video keywords without limiting ourselves to a particular video feature descriptor.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121584539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Soft biometric retrieval to describe and identify surveillance images 描述和识别监控图像的软生物特征检索

2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA) Pub Date : 2016-02-01 DOI: 10.1109/ISBA.2016.7477240

Daniel Martinho-Corbishley, M. Nixon, J. Carter

引用次数: 18

On motion-sensor behavior analysis for human-activity recognition via smartphones 基于智能手机的人体活动识别的运动传感器行为分析

2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA) Pub Date : 2016-02-01 DOI: 10.1109/ISBA.2016.7477231

Chao Shen, Yufei Chen, Gengshan Yang

{"title":"On motion-sensor behavior analysis for human-activity recognition via smartphones","authors":"Chao Shen, Yufei Chen, Gengshan Yang","doi":"10.1109/ISBA.2016.7477231","DOIUrl":"https://doi.org/10.1109/ISBA.2016.7477231","url":null,"abstract":"A wealth of sensors on smartphones has greatly facilitated people's life, which may also provide great potential for accurate human activity recognition. This paper presents an empirical study of analyzing the behavioral characteristics of smartphone inertial sensors for human activity recognition. The rationale behind is that different human activities would cause different levels of posture and motion change of smartphone. In this work, an Android application was run as a background job to monitor data of motion sensors. Sensory data from motion sensors (mainly including accelerometer and gyroscope data) were analyzed to extracted time-, frequency-, and wavelet-domain features for accurate and fine-grained characterization of human activities. Classification technique were applied to build both personalized model and generalized model for discriminating five daily human activities: going downstairs, going upstairs, walking, running, and jumping. Analyses conducted on 18 subjects showed that these human activities can be accurately recognized from smartphone-sensor behavior, with recognition rates expressed by the area under the ROC curve ranging from 84.97% to 90.65%. We also discuss a number of avenues for additional research to advance the state of the art in this area.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128685999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 32

Sitting posture diagnosis using a pressure sensor mat 使用压力传感垫进行坐姿诊断

2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA) Pub Date : 2016-02-01 DOI: 10.1109/ISBA.2016.7477236

Shunsuke Suzuki, Mineichi Kudo, Atsuyoshi Nakamura

引用次数: 11

Recognizing human faces under disguise and makeup 识别伪装和化妆后的人脸

2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA) Pub Date : 2016-02-01 DOI: 10.1109/ISBA.2016.7477243

Tsung Ying Wang, Ajay Kumar

{"title":"Recognizing human faces under disguise and makeup","authors":"Tsung Ying Wang, Ajay Kumar","doi":"10.1109/ISBA.2016.7477243","DOIUrl":"https://doi.org/10.1109/ISBA.2016.7477243","url":null,"abstract":"The accuracy of automated human face recognition algorithms can significantly degrade while recognizing same subjects under make-up and disguised appearances. Increasing constraints on enhanced security and surveillance requires enhanced accuracy from face recognition algorithms for faces under disguise and/or makeup. This paper presents a new database for face images under disguised and make-up appearances the development of face recognition algorithms under such covariates. This database has 2460 images from 410 different subjects and is acquired under real environment, focuses on make-up and disguises covariates and also provides ground truth (eye glass, goggle, mustache, beard) for every image. This can enable developed algorithms to automatically quantify their capability for identifying such important disguise attribute during the face recognition We also present comparative experimental results from two popular commercial matchers and from recent publications. Our experimental results suggest significant performance degradation in the capability of these matchers in automatically recognizing these faces. We also analyze face detection accuracy from these matchers. The experimental results underline the challenges in recognizing faces under these covariates. Availability of this new database in public domain will help to advance much needed research and development in recognizing make-up and disguised faces.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133534859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 40

Deep feature-based face detection on mobile devices 移动设备上基于深度特征的人脸检测

2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA) Pub Date : 2016-02-01 DOI: 10.1109/ISBA.2016.7477230

Sayantan Sarkar, Vishal M. Patel, R. Chellappa

引用次数: 38

Face alignment via an ensemble of random ferns 通过随机蕨类植物的集合进行面部对齐

2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA) Pub Date : 2016-02-01 DOI: 10.1109/ISBA.2016.7477237

Xiang Xu, S. Shah, I. Kakadiaris

引用次数: 7

Rendering or normalization? An analysis of the 3D-aided pose-invariant face recognition 呈现还是规范化?三维辅助姿态不变人脸识别分析

2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA) Pub Date : 2016-02-01 DOI: 10.1109/ISBA.2016.7477244

Yuhang Wu, S. Shah, I. Kakadiaris

引用次数: 23