天美传媒

Blind people; Clothing defect detection; Object detection

Introduction

Visual impairment, blindness, can have a significant impact on the psychological and cognitive functioning of an individual [1]. Several studies have shown that vision impairment is associated with a variety of negative health outcomes and a poor quality of life. Additionally, blindness currently affects a significant number of individuals, and thus it should not be assumed as a minor concern for society [2, 3]. According to a recent study, there are 33.6 million people worldwide suffering from blindness, which clearly shows the dimension of this population group.

The use of assistive technology can help in mitigating the negative effects of blindness and improve the quality of life of people who are blind. Although there has been a proliferation of smart devices and advancements in cutting-edge technology for blind people, most research efforts have been directed towards navigation, mobility, and object recognition, leaving aesthetics aside. The selection of clothing and preferred style for different occasions is a fundamental aspect of one’s personal identity [4, 5]. This has a significant impact on the way we perceive ourselves, and on the way we are perceived by others. Nonetheless, individuals who are blind may experience insecurity and stress when it comes to dressing-up due to a lack of ability to recognize the garments’ condition. This inability to perceive visual cues can make dressing-up a daily challenge. In addition, blind people may have a higher probability of clothing staining and tearing due to the inherent difficulties in handling objects and performing daily tasks [4].

The inability to visually inspect clothing for defects can be a frustrating experience for blind individuals, impacting their appearance, comfort, and overall confidence. Traditional methods, such as manual inspection or assistance from others, have limitations [6]. The emergence of object detection technology presents an exciting opportunity to address these challenges. This article aims to provide an overview of the use of object detection in identifying clothing defects for blind people.

This section provides an overview of existing approaches and systems that utilize object detection technology to identify clothing defects. Various methodologies, including supervised, unsupervised, and semi-supervised learning techniques, are explored [7, 8]. The article discusses popular datasets used for training and evaluating clothing defect detection models and presents a comparative analysis of different algorithms and architectures employed in the field. This section discusses the challenges and limitations associated with using object detection technology to identify defects in clothing for blind people. Factors such as occlusion, variation in clothing textures, realtime detection, and computational constraints are examined [9]. The importance of robust and scalable solutions is emphasized, along with the need for addressing ethical considerations and privacy concerns. In this section, potential future directions and advancements in the field of clothing defect detection for blind people are discussed. The article explores emerging technologies such as wearable devices, haptic feedback, and integration with assistive devices to enhance the user experience [10]. The incorporation of multi-modal approaches, including audio feedback and natural language processing, is also explored. This section highlights the significant impact that object detection technology can have on the lives of visually impaired individuals. By enabling independent detection of clothing defects [11], this technology promotes self-confidence, improves personal grooming, and enhances social integration. Real-life case studies and user testimonials further illustrate the positive outcomes of using object detection for blind people [12, 13].

Conclusion

Blind individuals face daily challenges with simple tasks, namely related to clothing and style, which are critical components of one’s personal identity. Assistance from family or friends is often required to support daily dressing-up tasks and, many times, such help is essential for detecting defects on clothes that, otherwise, would go unnoticed. Therefore, defect detection in clothing is of the utmost importance for blind individuals to feel comfortable and confident with their appearance. However, the recall values demonstrated that the model can still be improved to minimize false negatives. The detection of holes was found to be more challenging than the detection of stains, which emphasizes the importance of integrating the findings of this study in an automatic wardrobe that could take multiple images from the perspective of different clothing items.

In conclusion, object detection technology has the potential to revolutionize the way blind individuals detect defects in clothing. Despite current challenges, advancements in computer vision and machine learning offer promising solutions. Future research and development efforts should focus on refining existing methodologies, addressing limitations, and ensuring widespread accessibility to improve the overall quality of life for blind people in the fashion domain.

The dataset built in this work demonstrated that object detection technology can be used to accurately and autonomously detect and classify defects on clothing. Moreover, it represents the first step for the creation of a mobile application that can effectively detect multiple defects on clothing, based on the integration of these findings in an automated closet system as a future step. Overall, the main objective of this study was accomplished, since a system that enables blind people to automatically identify clothing and detect multiple defects in garments was successfully developed and tested, thereby providing them with greater independence and autonomy, while contributing to an improved quality of daily life.

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