检索结果-内蒙古大学图书馆

IEEE International Conference on Multimedia and Expo (ICME)

作者： Wang, Yan Li, Sheng Kot, Alex C. Nanyang Technol Univ Sch Elect & Elect Engn Rapid Rich Object Search ROSE Lab Singapore 639798 Singapore

ISBN: (纸本)9781479970827

Fashion recommendation helps shoppers to find desirable fashion items, which facilitates online interaction and product promotion. In this paper, we propose a method to recommend handbags to each shopper, based on the handbag images the shopper has clicked. This is performed by Joint learning of attribute Projection and One-class SVM classification (JPO) based on the images of the shopper's preferred handbags. More specifically, for the handbag images clicked by each shopper, we project the original image feature space into an attribute space which is more compact. The projection matrix is learned jointly with a one-class SVM to yield a shopper-specific one-class classifier. The results show that the proposed JPO handbag recommendation performs favorably based on initial subject testing.

关键词： Recommender system handbag one-class classification attribute joint learning

来源：评论

学校读者我要写书评

暂无评论

CONTROLlabLE AND GRADUAL FACIAL BLEMISHES RETOUCHING VIA PHYSICS-BASED MODELLING

CONTROLLABLE AND GRADUAL FACIAL BLEMISHES RETOUCHING VIA PHY...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Shuai, Chenhao Cai, Rizhao Dissanayake, Bandara Newman, Amanda Guan, Dayan Sng, Dennis Li, Ling Kot, Alex Nanyang Technol Univ NTU Singapore Singapore Procter & Gamble Co Cincinnati OH USA Rapid Rich Object Search ROSE Lab Singapore Singapore Nanyang Technol Univ NTU Sch Elect & Elect Engn Rapid Rich Object Search ROSE Lab Singapore Singapore

ISBN: (纸本)9798350390155;9798350390162

Face retouching aims to remove facial blemishes, such as pigmentation and acne, and still retain fine-grain texture details. Nevertheless, existing methods just remove the blemishes but focus little on realism of the intermediate process, limiting their use more to beautifying facial images on social media rather than being effective tools for simulating changes in facial pigmentation and ance. Motivated by this limitation, we propose our Controllable and Gradual Face Retouching (CGFR). Our CGFR is based on physical modelling, adopting Sum-of-Gaussians to approximate skin subsurface scattering in a decomposed melanin and haemoglobin color space. Our CGFR offers a user-friendly control over the facial blemishes, achieving realistic and gradual blemishes retouching. Experimental results based on actual clinical data shows that CGFR can realistically simulate the blemishes' gradual recovering process.

关键词： Facial blemish retouching Physical modelling

来源：评论

学校读者我要写书评

暂无评论

Exploring Local and Overall Ordinal Information for Robust Feature Description

引用

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2016年第11期38卷 2198-2211页

作者： Wang, Zhenhua Fan, Bin Wang, Gang Wu, Fuchao Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing Peoples R China Nanyang Technol Univ Sch Elect Elect Engn Rapid Rich Object Search Lab Singapore Singapore

This paper aims to build robust feature descriptors by exploring intensity order information in a patch. To this end, the local intensity order pattern (LIOP) and the overall intensity order pattern (OIOP) are proposed to effectively encode intensity order information of each pixel in different aspects. Specifically, LIOP captures the local ordinal information by using the intensity relationships among all the neighbouring sampling points around a pixel, while OIOP exploits the coarsely quantized overall intensity order of these sampling points. These two kinds of patterns are then separately aggregated into different ordinal bins, leading to two kinds of feature descriptors. Furthermore, as these two kinds of descriptors could encode complementary ordinal information, they are combined together to obtain a discriminative and compact mixed intensity order pattern descriptor. All these descriptors are constructed on the basis of relative relationships of intensities in a rotationally invariant way, making them be inherently invariant to image rotation and any monotonic intensity changes. Experimental results on image matching and object recognition are encouraging, demonstrating the superiorities of our descriptors over the state of the art.

关键词： Feature description intensity order illumination invariance image matching

来源：评论

学校读者我要写书评

暂无评论

Person Reidentification Using Multiple Egocentric Views

引用

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2017年第3期27卷 484-498页

作者： Chakraborty, Anirban Mandal, Bappaditya Yuan, Junsong Nanyang Technol Univ Sch Elect & Elect Engn Rapid Rich Object Search Lab Singapore 639798 Singapore Agcy Sci Technol & Res Inst Infocomm Res Singapore 138632 Singapore

Development of a robust and scalable multicamera surveillance system is the need of the hour to ensure public safety and security. Being able to reidentify and track one or more targets over multiple nonoverlapping camera field of views in a crowded environment remains an important and challenging problem because of occlusions, large change in the viewpoints, and illumination across cameras. However, the rise of wearable imaging devices has led to new avenues in solving the reidentification (re-id) problem. Unlike static cameras, where the views are often restricted or low resolution and occlusions are common scenarios, egocentric/first person views (FPVs) mostly get zoomed in, unoccluded face images. In this paper, we present a person re-id framework designed for a network of multiple wearable devices. The proposed framework builds on commonly used facial feature extraction and similarity computation methods between camera pairs and utilizes a data association method to yield globally optimal and consistent re-id results with much improved accuracy. Moreover, to ensure its utility in practical applications where a large amount of observations are available every instant, an online scheme is proposed as a direct extension of the batch method. This can dynamically associate new observations to already observed and labeled targets in an iterative fashion. We tested both the offline and online methods on realistic FPV video databases, collected using multiple wearable cameras in a complex office environment and observed large improvements in performance when compared with the state of the arts.

关键词： Egocentric videos face recognition multicamera surveillance person reidentification (re-id) wearable devices

来源：评论

学校读者我要写书评

暂无评论

DeepBag: Recognizing Handbag Models

引用

IEEE TRANSACTIONS ON MULTIMEDIA 2015年第11期17卷 2072-2083页

作者： Wang, Yan Li, Sheng Kot, Alex C. Nanyang Technol Univ Sch Elect & Elect Engn Rapid Rich Object Search ROSE Lab Singapore 637553 Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

In this paper, we address the problem of branded handbag recognition. It is a challenging problem due to the non-rigid deformation, illumination changes, and inter-class similarity. We propose a novel framework based on deep convolutional neural network (CNN). Concretely, we propose a new CNN model, called feature selective joint classification-regression CNN (FSCR-CNN). Its advantages lie in two folds: 1) it alleviates the illumination changes by a feature selection strategy to focus on the color-nondiscriminative features in the network learning, and 2) rather than only targeting on the hard label (i.e., the handbag model), it also incorporates a soft label (i.e., a distribution measuring the similarity between the ground truth model and all the models to be trained) to construct the loss function for training CNN, which leads to a better classifier for handbags with large inter-class similarity. We evaluate the performance of our framework on a newly built branded handbag dataset. The results show that it performs favorably for recognizing handbags with 94.48% in accuracy. We also apply the proposed FSCR-CNN model in recognizing other fine-grained objects with state-of-the-art CNN architectures, which is able to achieve over 5% improvement in accuracy.

关键词： Convolutional neural networks feature selection handbag recognition soft label

来源：评论

学校读者我要写书评

暂无评论

Deep Multimodal Sequence Fusion by Regularized Expressive Representation Distillation

引用

IEEE TRANSACTIONS ON MULTIMEDIA 2023年 25卷 2085-2096页

作者： Guo, Xiaobao Kong, Adams Wai-Kin Kot, Alex Nanyang Technol Univ Singapore Sch Comp Sci & Engn Singapore 639798 Singapore Nanyang Technol Univ Interdisciplinary Grad Programme Rapid Rich Object Search ROSE Lab Singapore 639798 Singapore

Multimodal sequence learning aims to utilize information from different modalities to enhance overall performance. Mainstream works often follow an intermediate-fusion pipeline, which explores both modality-specific and modality-supplementary information for fusion. However, the unaligned and heterogeneously distributed multimodal sequences pose significant challenges to the fusion task: 1) to extract both effective unimodal and crossmodal representations and 2) to overcome the overfitting issue in joint multimodal sequence optimization. In this work, we propose regularized expressive representation distillation (RERD) that aims to seek effective multimodal representations and to enhance the generalization of fusion. First, to improve unimodal representation learning, unimodal representations are assigned to multi-head distillation encoders, where the unimodal representations are iteratively updated through distillation attention layers. Second, to alleviate the overfitting issue in joint crossmodal optimization, a multimodal sinkhorn distance regularizer is proposed to reinforce the expressive representation extraction and to reduce the modality gap before fusion adaptively. These representations produce a comprehensive view of the multimodal sequences, which are utilized for downstream fusion tasks. Experimental results on several popular benchmarks demonstrate that the proposed method achieves state-of-the-art performance, compared with widely used baselines for deep multimodal sequence fusion, as shown in https://***/Redaimao/RERD.

关键词： Multimodal sequence fusion multimodal sentiment analysis regularization

来源：评论

学校读者我要写书评

暂无评论

On Branded Handbag Recognition

引用

IEEE TRANSACTIONS ON MULTIMEDIA 2016年第9期18卷 1869-1881页

作者： Wang, Yan Li, Sheng Kot, Alex C. Nanyang Technol Univ Sch Elect & Elect Engn Rapid Rich Object Search ROSE Lab Singapore 637553 Singapore Shanghai Univ Sch Commun & Informat Engn Shanghai 200444 Peoples R China

Manufacturing branded handbags is a big business in the fashion world. Shoppers' feedback showing photos of their purchased handbags in social networks or blogs is important for branding purposes. In this paper, we deal with handbag recognition. It is a challenging problem due to the inter-class style similarity and the intra-class color variation. We focus on developing discriminative representations of handbag style and color. For handbag style representation, two supervised mid-level patch selection procedures are proposed to select discriminative patches, regarding individual classes and pairwise classes. We also propose a low-level complementary feature, extracted from texture-enhanced mid-level patches, to capture the fine details of the mid-level patches. For handbag color representation, we propose to extract dominant color features to handle the illumination changes. The performance of our proposed method is evaluated on a newly built branded handbag dataset. The results show that our method performs favorably in recognizing handbags, with around 10% improvement in accuracy when compared with the existing fine-grained or generic object recognition methods.

关键词： Branded handbag recognition discriminative fine-grained object recognition

来源：评论

学校读者我要写书评

暂无评论

QUALITY ASSESSMENT OF MULTI-VIEW-PLUS-DEPTH IMAGES

QUALITY ASSESSMENT OF MULTI-VIEW-PLUS-DEPTH IMAGES

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Wang, Jiheng Wang, Shiqi Zeng, Kai Wang, Zhou Univ Waterloo Dept Elect & Comp Engn Waterloo ON Canada Nanyang Technol Univ Rapid Rich Object Search Lab Singapore Singapore

ISBN: (纸本)9781509060672

Multi-view-plus-depth (MVD) representation has gained significant attention recently as a means to encode 3D scenes, allowing for intermediate views to be synthesized on-the-fly at the display site through depth-image-based-rendering (DIBR). Automatic quality assessment of MVD images/videos is critical for the optimal design of MVD image/video coding and transmission schemes. Most existing image quality assessment (IQA) and video quality assessment (VQA) methods are applicable only after the DIBR process. Such post-DIBR measures are valuable in assessing the overall system performance, but are difficult to be directly employed in the encoder optimization process in MVD image/video coding. Here we make one of the first attempts to develop a perceptual pre-DIBR IQA approach for MVD images by employing an information content weighted approach that balances between local quality measures of texture and depth images. Experiment results show that the proposed approach achieves competitive performance when compared with state-of-the-art IQA algorithms applied post-DIBR.

关键词： 3D image image quality assessment depth-image-based-rendering multi-view-plus-depth

来源：评论

学校读者我要写书评

暂无评论

Fast Appearance Modeling for Automatic Primary Video object Segmentation

引用

IEEE TRANSACTIONS ON IMAGE PROCESSING 2016年第2期25卷 503-515页

作者： Yang, Jiong Price, Brian Shen, Xiaohui Lin, Zhe Yuan, Junsong Nanyang Technol Univ Rapid Rich Object Search Lab Singapore 637553 Singapore Adobe Res San Jose CA 95110 USA Nanyang Technol Univ Dept Elect & Elect Engn Singapore 639798 Singapore

Automatic segmentation of the primary object in a video clip is a challenging problem as there is no prior knowledge of the primary object. Most existing techniques thus adapt an iterative approach for foreground and background appearance modeling, i.e., fix the appearance model while optimizing the segmentation and fix the segmentation while optimizing the appearance model. However, these approaches may rely on good initialization and can be easily trapped in local optimal. In addition, they are usually time consuming for analyzing videos. To address these limitations, we propose a novel and efficient appearance modeling technique for automatic primary video object segmentation in the Markov random field (MRF) framework. It embeds the appearance constraint as auxiliary nodes and edges in the MRF structure, and can optimize both the segmentation and appearance model parameters simultaneously in one graph cut. The extensive experimental evaluations validate the superiority of the proposed approach over the state-of-the-art methods, in both efficiency and effectiveness.

关键词： Automatic primary video object segmentation graph cut appearance modeling

来源：评论

学校读者我要写书评

暂无评论

Color Space Learning for Cross-Color Person Re-Identification

Color Space Learning for Cross-Color Person Re-Identificatio...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Nie, Jiahao Lin, Shan Kot, Alex C. Nanyang Technol Univ Interdisciplinary Grad Programme Singapore Singapore Nanyang Technol Univ Rapid Rich Object Search ROSE Lab Singapore Singapore

ISBN: (纸本)9798350390155;9798350390162

The primary color profile of the same identity is assumed to remain consistent in typical Person Re-identification (Person ReID) tasks. However, this assumption may be invalid in real-world situations and images hold variant color profiles, because of cross-modality cameras or identity with different clothing. To address this issue, we propose Color Space Learning (CSL) for those Cross-Color Person ReID problems. Specifically, CSL guides the model to be less color-sensitive with two modules: Image-level Color-Augmentation and Pixel-level Color-Transformation. The first module increases the color diversity of the inputs and guides the model to focus more on the non-color information. The second module projects every pixel of input images onto a new color space. In addition, we introduce a new Person ReID benchmark across RGB and Infrared modalities, NTU-Corridor, which is the first with privacy agreements from all participants. To evaluate the effectiveness and robustness of our proposed CSL, we evaluate it on several Cross-Color Person ReID benchmarks. Our method surpasses the state-of-the-art methods consistently. The code and benchmark are available at: https://***/niejiahao1998/CSL

关键词： Person Re-Identification Benchmark

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：