Learning and Recognition of Clothing Genres From Full-Body Images

Hidayati, Shintami Chusnul; You, Chuang-Wen; Cheng, Wen-Huang; Hua, Kai-Lung

doi:10.1109/tcyb.2017.2712634

Cited by 46 publications

(26 citation statements)

References 30 publications

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“…Jarin Joe Rini et al [11] have proposed automatically recognizingclothspatternsandcolors.Theyhaveused the CCNY clothing dataset. The patterns in the clothinggenresareclassifiedusingtheSupportVector Machine (SVM) algorithm.Hidayatiet al [1] have proposed a novel approach for automatically classifying upper wear and lower wear genres based on the different style elements present on the clothing genres. For this purpose collect full-body human images from various online websites like Amazon, Zara .Then perform body parts detection using human body part detector [15] [16].…”

Section: Image Based Clothingclassification Techniquesmentioning

confidence: 99%

Clothing Genre Recognition System Using Image Processing Techniques- A Survey

Saranya¹,

Geetha²

2021

Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICA

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Nowadays, Clothing business is one of the mostimportantcomponentsinthee-commerceindustry. So, there is plenty of online clothing sites are available where people can search and retrieve the most clothing items for their user query image. Clothing genre recognition is a very active topic in computer vision and multimedia research. In the textile industry, image processing techniques provide sensitive attention in the fieldoftheimage-basedclothingrecognitionsystem.The sequence of cloth images can be given as input to the recognition system. This clothing genre recognition system helps to detect the patterns and features of cloths which helps to classify them using effective feature extraction and classification algorithms. Feature extractiontechniquescanbeusedtoobtainfeaturesfrom thecloths.Classificationalgorithmsfromsoftcomputing help to automatically classify clothes genres depending on style elements and their salient visual features. Deep learning and Support Vector Machine (SVM) classifier achieved better performance in classifying both upper wear and lower wear genres. The main motivations of this paper focus on automatically classifying both upper wearandlowerweargenrefromafull-bodyinputimage. Evaluation metrics like precision, recall, F-score were used to measure the classification accuracy.This paper addresses on issues, challenges, applications, frameworks, tools, and techniques for recognition of clothing genres is carriedout.

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Section: Image Based Clothingclassification Techniquesmentioning

confidence: 99%

Clothing Genre Recognition System Using Image Processing Techniques- A Survey

Saranya¹,

Geetha²

2021

Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICA

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“…Li et al [22] proposed a recognition framework that is based on multiple sources of features and ELM neural networks. Hidayati et al [23] presented a novel approach for automatically classifying clothing genres using the visually differentiable style elements. Yang and Yu [24] proposed a video content analysis framework to locate the people's position, frame the clothing regions, and identify the category of the clothing.…”

Section: Related Workmentioning

confidence: 99%

Clothing Attribute Recognition Based on RCNN Framework Using L-Softmax Loss

et al. 2020

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“…Clothing recognition has been used for fashion purposes [25,26], pedestrian profiling [24,29] and also to reaffirm the decision for gender recognition [24]. The clothing also has been used for criminal identification [6].…”

Section: Clothing Recognitionmentioning

confidence: 99%

A Review of Content-Based Video Retrieval Techniques for Person Identification

Ridzuan¹,

Omar²,

Sheikh³

2019

Elektrika

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The rise of technology spurs the advancement in the surveillance field. Many commercial spaces reduced the patrol guard in favor of Closed-Circuit Television (CCTV) installation and even some countries already used surveillance drone which has greater mobility. In recent years, the CCTV Footage have also been used for crime investigation by law enforcement such as in Boston Bombing 2013 incident. However, this led us into producing huge unmanageable footage collection, the common issue of Big Data era. While there is more information to identify a potential suspect, the massive size of data needed to go over manually is a very laborious task. Therefore, some researchers proposed using Content-Based Video Retrieval (CBVR) method to enable to query a specific feature of an object or a human. Due to the limitations like visibility and quality of video footage, only certain features are selected for recognition based on Chicago Police Department guidelines. This paper presents the comprehensive reviews on CBVR techniques used for clothing, gender and ethnic recognition of the person of interest and how can it be applied in crime investigation. From the findings, the three recognition types can be combined to create a Content-Based Video Retrieval system for person identification.

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Learning and Recognition of Clothing Genres From Full-Body Images

Cited by 46 publications

References 30 publications

Clothing Genre Recognition System Using Image Processing Techniques- A Survey

Clothing Genre Recognition System Using Image Processing Techniques- A Survey

Clothing Attribute Recognition Based on RCNN Framework Using L-Softmax Loss

A Review of Content-Based Video Retrieval Techniques for Person Identification

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