Video Captioning on Edge as Blind Assistant System
| dc.contributor.author | Mohammed Adnan Khan 1NH20CE028; Shreesha J M 1NH20CE047 | |
| dc.date.accessioned | 2025-05-31T10:20:48Z | |
| dc.date.available | 2025-05-31T10:20:48Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | The wearable device presents an innovative solution tailored to address the unique challenges faced by individuals with visual impairments. Positioned near the head and equipped with an earphone, it serves as a versatile aid, offering real-time auditory guidance to users. Upon activation, the device harnesses the power of computer vision and machine learning algorithms, all executed locally on the Edge, eliminating the need for external communication. Central to the device's functionality is its ability to classify objects encountered by the user. Through sophisticated machine learning algorithms, it swiftly identifies and categorizes objects in the user's vicinity, providing crucial information for navigation and obstacle avoidance. This feature not only enhances safety but also promotes independence by enabling users to navigate their surroundings with confidence. In addition to object classification, the device incorporates facial recognition technology, allowing it to identify individuals who come into the user's proximity. The device's object description functionality bridges the gap between visual data and auditory feedback, providing users with comprehensive descriptions of identified objects in real-time. This enables users to perceive their surroundings more fully and make informed decisions about navigation and interaction. By leveraging the power of machine learning and executing computations on the Edge, it offers a high degree of accuracy and efficiency while promoting user independence and autonomy. As technology continues to evolve, solutions like these have the potential to greatly improve the quality of life for individuals with visual impairments, enabling them to navigate the world with greater confidence and ease. Overall, this innovative wearable device stands as a testament to the profound impact that well-designed assistive technology can have on enhancing the quality of life, promoting independence, and fostering a greater sense of autonomy for individuals with visual impairments. | |
| dc.identifier.uri | http://192.168.75.5:4000/handle/123456789/19196 | |
| dc.language.iso | en | |
| dc.publisher | NHCE | |
| dc.title | Video Captioning on Edge as Blind Assistant System | |
| dc.type | Learning Object |