Interactive Human 3D Model with Conventional AI

Abstract

The convergence of interactive human 3D models with conventional artificial intelligence (AI) represents a groundbreaking fusion of computer graphics and intelligent systems. This interdisciplinary field combines advanced 3D modeling techniques with classical AI methodologies to create interactive virtual representations of humans. Rigorous studies in 3D modeling and animation form the basis for lifelike avatars, while conventional AI empowers these models with the ability to understand user inputs, make contextually relevant decisions, and engage in dynamic and responsive interactions. At the heart of this innovation is the emphasis on human-computer interaction (HCI), leveraging principles such as gesture recognition, voice commands, and user-friendly interfaces to enhance user experiences. The integration extends into virtual and augmented reality (VR/AR), providing users with immersive and engaging environments where interactive 3D human models come to life. Applications of this technology span a wide array of fields, including virtual companionship, education, healthcare simulations, entertainment, and training scenarios. The impact is transformative, offering new possibilities for human-machine interactions and redefining traditional approaches to AI applications. However, the burgeoning field is not without challenges. Privacy concerns, ethical considerations related to realistic human representation, and the societal impact of interactive 3D models necessitate careful examination. This abstract provides a glimpse into the technical intricacies of creating lifelike models, the intelligence driving their interactive capabilities, and the broader implications for diverse applications and industries. As research and development progress, the collaboration of computer graphics and AI not only opens new avenues but also prompts a thoughtful reevaluation of the evolving relationship between humans and intelligent, interactive 3D representations.

Introduction

I. INTRODUCTION

In the rapidly evolving landscape of human-computer interaction, the integration of advanced technologies such as 3D modeling and artificial intelligence (AI) is paving the way for more immersive and intuitive user experiences. This paper presents a comprehensive overview of our project, which centers on the development of an interactive 3D human model using React and Three.js libraries. The model is designed to engage users in a dynamic and conversational manner by leveraging the capabilities of ChatGPT, an advanced natural language processing AI developed by OpenAI.

The primary objective of this project is to create a seamless interaction where users can type their queries, and the 3D model responds with spoken answers. This is achieved through a robust architecture that processes user inputs, interacts with ChatGPT for generating appropriate responses, and utilizes speech synthesis to deliver the answers audibly. Additionally, the application is equipped with a feature that stores the user's search history, providing a valuable record of interactions for future reference.

By integrating these technologies, our project not only enhances the user experience through realistic and engaging interactions but also demonstrates the potential of combining 3D visualization with AI-driven communication. This paper will delve into the technical aspects of the project, including the implementation of the 3D model, the integration of ChatGPT, and the storage and management of search history. Through this exploration, we aim to highlight the innovative aspects and practical applications of our work in the realm of human-computer interaction.

The integration of interactive human 3D models with conventional artificial intelligence (AI) marks a compelling intersection of computer graphics, artificial intelligence, and humancomputer interaction. In recent years, advancements in technology have propelled the creation of realistic, lifelike 3D representations of humans, while conventional AI techniques have been harnessed to imbue these models with interactive and intelligent behaviors. This innovative field holds the promise of transforming how we engage with virtual entities, enabling more immersive and natural interactions. The amalgamation of sophisticated 3D modeling techniques and classical AI approaches opens avenues for applications ranging from virtual companions and educational tools to healthcare simulations and beyond. The applications of this technology are far-reaching. Virtual companions can provide emotional support, educational simulations can offer lifelike learning experiences, and healthcare scenarios can benefit from realistic patient interactions. The impact extends to entertainment, training, and various industries seeking innovative ways to leverage AI and 3D modeling. 

Challenges and Ethical Considerations As with any pioneering field, challenges abound. Ensuring privacy, addressing ethical concerns related to the realistic representation of humans, and understanding the social implications of interactive 3D models are crucial considerations that researchers and developers must navigate. The scope of interactive human 3D models with conventional AI is expansive, promising a paradigm shift in how we interact with virtual entities. This exploration delves into the technical intricacies of creating lifelike models, the intelligence driving their interactive capabilities, and the broader implications for diverse applications and industries.  

As we delve deeper into this domain, the collaboration of computer graphics and AI not only opens new avenues for research and development but also challenges our ethical and societal norms, prompting a thoughtful examination of the evolving relationship between humans and intelligent, interactive 3D representations. 

II. LITERATURE SURVEY

In the paper[1], this research focuses on the work is to build a versatile virtual-guide system adaptable to the user needs of mobility and therefore usable on different device (e.g. PDAs, Smartphones). An information retrieval service is included and is easily accessible through a spoken language interaction. The system takes the advantages of chatbot and speech recognition technologies, allowing a natural interaction with the user. 

In this paper[2] we investigate the effects of IVA embodiment on collaborative decision making. In a within-subjects study, participants performed a desert survival task in three conditions: (1) performing the task alone, (2) working with a disembodied voice assistant, and (3) working with an embodied assistant.

Our results show that both assistant conditions led to higher performance over when performing the task alone, but interestingly the reported task load with the embodied assistant was significantly lower than with the disembodied voice assistant. We discuss the findings with implications for effective and efficient collaborations with IVAs while also emphasizing the increased social presence and richness of the embodied assistant 

In this paper [3] Virtual assistants are improving and providing consumers with greater advantages. The comprehension and fulfilment of requests by virtual assistants will increase as voice recognition and natural language processing continue to grow. Virtual assistants are projected to be employed in more commercial activities as speech recognition technology advances. The main goal of developing personal assistant software (virtual assistant) is to use webbased semantic data sources, user-generated content, and knowledge from knowledge libraries. Basically, main objective of making this VoiceBased Virtual Assistant is to make life easier and having a personal assistant to everyone which can perform many tasks.  

In this paper [4], this research with the advancements in speech recognition and AI technology, there is a growing demand for convenient and efficient ways to interact with technology. A Voice-based

Virtual Assistant is a technologically advanced solution that uses speech recognition and artificial intelligence to provide users with a convenient and efficient way to interact with devices, access information, and perform tasks. 

In this paper [5], one of the goals of Artificial intelligence (AI) is the realization of natural dialogue between humans and machines. in recent years, the dialogue systems, also known as interactive conversational systems are the fastest growing area in AI. Many companies have used the dialogue systems technology to establish various kinds of Virtual Personal Assistants(VPAs) based on their applications and areas, such as Microsoft’s Cortana, Apple’s Siri, Amazon Alexa, Google Assistant, and Facebook’s M. However, in this proposal, we have used the multi-modal dialogue systems which process two or more combined user input modes, such as speech, image, video, touch, manual gestures, gaze, and head and body movement. 

In this paper[6], The motive of this paper is to develop an IOT based elegant reflector using Raspberry PI. IOT plays a major role in connecting every technological environment with human life. The elegant reflector used here operators based on voice command inputs and identity verification of the individual. .In short it works like a personal assistant for the human to  make their life very sophisticated .The reflector uses an infrared module which always remains in "on state" ,when the individuals come in front of the reflector it senses the heat of the users body and approaches the online state. The coding languages such as php, Html and python are required to display he webpage contents in the elegant reflector .The future work ofthis system may also include different types of sensors ,ray optics ,image processing systems by advancing them in various fields like health care ,restaurants , airports , etc , .Other than home automation.

III. PROPOSED DESIGN

The proposed system is a human 3D Model that help to create an immersive and dynamic interaction between the users and virtual characters. While conventional artificial intelligence (AI) techniques have made significant strides in generating 3D models, there are persistent challenges that hinder the achievement of highly accurate, detailed, and contextually relevant human representations. 

The Objective of this project is to develop a system that integrates a 3D human model with a conversational AI to create an The primary goal is to create an engaging and immersive user experience where users can interact with a lifelike 3D human model that responds to their queries and conversations powered by a ChatGPT AI. Natural Language Processing, and user experience design. It aims to create an innovative and immersive conversational experience for users while maintaining a visually appealing  and responsive 3D model.

The problem statement involves creating a human 3D model that is intricately linked to a chatbot powered by ChatGPT. This integration will be implemented using ReactJS. The challenge lies in seamlessly combining the interactive 3D model with the chat interface to enhance user engagement and provide a more immersive experience. This entails handling real-time updates and synchronization between the 3D model and the chatbot, ensuring a smooth and responsive user interaction.  Additionally, considerations should be made for user input affecting the 3D model and vice versa, creating a cohesive and dynamic user experience. The goal is to leverage ReactJS to build an intuitive and visually appealing interface that effectively combines the capabilities of a human 3D model with the conversational abilities of ChatGPT. The result of linking a human 3D model to ChatGPT using ReactJS would be a dynamic and immersive user experience where users can engage in natural language conversations with an AI-powered chatbot while simultaneously interacting with a visually appealing 3D representation of a human.

The result of this integration is a modern and interactive application that leverages the strengths of conversational AI (ChatGPT), 3D modeling, and the ReactJS framework to deliver a unique and engaging user experience. 

A. Start

Initialization: The system initializes necessary components, such as loading configurations, setting up connections to databases or external APIs, and preparing any required resources.

Environment Check: Verify that the system environment is correctly set up and ready to process user inputs.

B. User Input

Input Interface: The system presents an interface (e.g., a text box, voice input) where the user can enter their query.

Input Validation: Preliminary checks to ensure that the input meets basic criteria (e.g., not empty, within character limits).

C. Store History

Logging: The user input is logged into a database or file system. This may include additional metadata like timestamps, user ID, and session ID.

Purpose: Storing history can be useful for analytics, improving the system, debugging, and providing personalized experiences.

D. Query

Validity Check: The system evaluates whether the query is valid. This might include syntax checking, ensuring it adheres to expected formats, or validating against known criteria.

False: If the query is invalid:

Error Display: A specific error message is generated and displayed to the user.

Feedback Loop: Optionally, the system might provide suggestions on how to correct the query. True: If the query is valid, the system proceeds to processing.

E. Process The Query

Parsing: The query is parsed to understand its intent and extract relevant information.

Resource Allocation: Allocate necessary resources to handle the query (e.g., access databases, call external APIs).

Business Logic: Apply the core logic of the system to process the query. This might involve computations, data retrieval, and applying algorithms.

F. Generating The Response

Response Formation: Construct the response based on the results of the query processing. This could be in the form of text, visual data, or other media.

Quality Check: Ensure the response is accurate, complete, and relevant to the user’s query. Formatting: Format the response in a way that is easily understandable by the user.

G. Display Response

User Interface: Present the response to the user through the interface. This might involve updating a web page, sending a message, or displaying a notification.

Interactivity: Optionally, the response might include interactive elements, such as links, buttons, or followup questions. 8. END

Clean-up: Release any resources that were allocated for processing the query.

Session Management: If the system uses sessions, manage the session state appropriately (e.g., keep it alive, terminate it).

Readiness for Next Query: Ensure the system is ready to handle the next user input without delays or issues.

H. Additional Considerations

Error Handling: Throughout this process, robust error handling is critical to manage unexpected issues gracefully and maintain a good user experience.

Security: Ensure that user data is handled securely, especially when storing history and processing queries.

Performance: Optimize each step to handle queries efficiently, minimizing latency and resource usage.

Scalability: Design the system to handle increasing loads as more users interact with it.

Feedback and Learning: Implement mechanisms to learn from user interactions, which can help improve the system over time through machine learning or rule updates.

By breaking down each step with these detailed explanations, you can better understand how to implement and refine a user query handling system.

V. ACKNOWLEDGEMENT

We take this opportunity to thank our project guide Prof. Kashmira Jayakar and Head of the Department Prof. Saurabh Parhad for their valuable guidance and for providing all the necessary facilities, which were indispensable in the completion of this project report. We are also thankful to all the staff members of the Department of Information Technology of RMD Sinhgad School of Engineering, Warje for their valuable time, support, comments, suggestions and persuasion. We would also like to thank the institute for providing the required facilities, Internet access and important books.

Conclusion

In this era of growing technology, Artificial Intelligence is the potential future and we realized that creating a virtual Assistant integrated with Artificial Intelligence a unique idea and very useful. It is valuable as a personal assistant as well as depicts a large potential use in different industries. The domain of Artificial Intelligence has increased by integrating it with a human 3D virtual assistant. Creating a 3D model of a human linked to a chatbot like GPT-3.5 could have various applications in virtual environments, gaming, or simulations. In the future, we wish to improve our platform even better and enhance its efficiency further.

References

[1] S. Arora, K. Batra,and S. Singh. Dialogue System: A Brief Review. Punjab Technical University. [2] R.Mead. 2017.Semio: Developing a Cloud-based Platform for Multimodal Conversational AI in Social Robotics. 2017 IEEE International Conference on Consumer Electronics (ICCE). [2] K. Noda, H. Arie, Y. Suga,and T. Ogata. 2014.Multimodal integration learning of robot using deep neural networks. Elsevier: Robotic and Autonomous Systems. [3] R. Pieraccini, K. Dayanidhi, J. Bloom, J. Dahan, M.l Phillips. 2003. A Multimodal Interface for a Concept Vehicle. Eurospeech 2003. [4] G. Bohouta and V. Z Këpuska. 2017. Comparing Speech Recognition Systems (Microsoft API, Google API And CMU Sphinx). Int. Journal of Engineering Research and Application 2017. [5] Khushboo Sharma, Disha Bahal, Aman Sharma, Ankita Garg, Neeta Verma, “ARA- A Voice Assistant for Disabled Personalities”, Internatonal Journal of Engineering Applied Sciences and Technology, 2022, Vol. 7, Issue 1, ISSN No. 2455-2143, Pages 106109 [6] Kshama V. Kulhalli ,Kotrappa Sirbi, Abhijit J. Patankar, “Personal Assistant with Voice Recognition Intelligence”, International Journal of Engineering Research and Technology. ISSN 0974-3154 Volume [7] 10, Number 1 (2017) [8] Pritam Kakde, Piyush Shah, Anmol Meshram, Yogesh Umap, Yogendra Misal, Akhil Anjikar “JARVIS - The Virtual Assistant”, International Research Journal of Modernization in Engineering Technology and Science, Volume:04/Issue:05/May-2022 [9] [Saunshimath, Nirmala & Thakur, Sakshi & Singh, Shrooti & Singh, Ranavijay & .K, Kumuda.(2022). SAHARA -A Smart Personal Assistant. 10.13140/RG.2.2.33808.48642

Copyright

Copyright © 2024 Kashmira Jayakar, Payal Sonawane, Samruddhi Shirke, Shubham Garkar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.