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

The integration of interactive human 3D models with conventional artificial intelligence (AI) marks a compelling intersection of computer graphics, artificial intelligence, and human-computer 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. RELATED WORK

1. A. Santangelo1, A. Augello1, A. Gentile-In this paper, 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.
2. Kangsoo Kim, Celso M. de Melo -In this paper 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
3. Satya Prakash Yadav-In this paper 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 web-based semantic data sources, user-generated content, and knowledge from knowledge libraries. Basically, main objective of making this Voice-Based Virtual Assistant is to make life easier and having a personal assistant to everyone which can perform many tasks.
4. Dr. M. Rajeswari-In this paper, 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.
5. Veton Ke?puska -In this paper, 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.

III. FLOWCHART

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 immersive and dynamic interaction between the users and virtual characters.

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. The success of the implementation depends on the seamless coordination of these components and the alignment with the application's goals and user expectations.

The architecture of an interactive 3D human model with a conventional artificial intelligence (AI) system involves various components working together to create a seamless and responsive user experience. Below is a high-level architectural overview:

1. User Interface (UI):

• Input Handling: Receives input from users through devices like keyboards, mice, and possibly voice and gesture recognition sensors.
• UI Controls: Interfaces for users to manipulate and control the 3D human model, such as buttons, sliders, and menus.

2. 3D Model Rendering:

• 3D Engine: Manages the rendering of the 3D human model, including handling graphics, textures, lighting, and animations.
• Physics Engine (optional): Simulates realistic movements and interactions of the 3D model.

3. Artificial Intelligence (AI) Components:

• Facial Recognition Module: Identifies facial features and expressions.
• Gesture Recognition Module: Processes user gestures to control the model.

4. AI Controller:

• Decision-Making Module: Uses AI algorithms to make decisions based on user input and context.
• Learning Algorithm (optional): Adapts the system's behavior over time through machine learning, improving responsiveness.

5. Data Management:

• 3D Model Data: Stores information about the 3D human model, including geometry, textures, and animations.
• AI Training Data: Datasets used for training AI modules.

6. Communication:

• Internal Communication: Ensures smooth communication between different components within the system.
• External Communication: Interfaces with external services or databases for additional data or functionalities.

7. User Feedback:

• Output Display: Presents the 3D human model and AI responses to the user.
• Feedback Mechanism: Provides feedback to the user based on interactions and AI-generated responses.

8. Security and Privacy:

• Security Layer: Implements measures to secure user data, especially if dealing with facial recognition or other sensitive information.
• Privacy Controls: Allows users to control and manage their data privacy settings.

9. Scalability and Performance Optimization:

• Parallel Processing: Utilizes parallel processing for computationally intensive tasks.
• Load Balancing (optional): Distributes the workload efficiently across servers or computing resources.

10. Cross-Platform Compatibility:

• Platform Abstraction Layer: Ensures compatibility across different operating systems and hardware configurations.

11. Logging and Analytics:

• Logging Mechanism: Records system events, errors, and user interactions for debugging and analysis.
• Analytics Module: Gathers data on user behavior and system performance for continuous improvement.

12. Documentation and Maintenance:

• Documentation: Provides comprehensive documentation for developers and users.
• Maintenance Module: Allows for easy updates and maintenance of the system.

This architecture can be implemented using a variety of programming languages, libraries, and frameworks based on the specific requirements and preferences of the development team. Additionally, it's important to consider modularity and flexibility in the design to accommodate future updates and improvements.

IV. ACKNOWLEDGMENT

The completion of the research on "Interactive Human 3D Model with Conventional AI" has been a collaborative effort, and we extend our heartfelt appreciation to those who have played a pivotal role in this endeavor. We express our deepest gratitude to our mentors and advisors, whose expertise and guidance have been indispensable throughout the entire research process. Their insightful feedback, encouragement, and unwavering support have significantly contributed to the refinement and success of this project. Our appreciation also goes to our colleagues and fellow researchers who have engaged in thought-provoking discussions, shared valuable insights, and provided constructive critiques. Their collaborative spirit has enriched the depth and scope of our exploration in this intricate intersection of computer graphics and artificial intelligence. Special thanks to the academic institutions and research organizations that have provided the necessary resources, infrastructure, and intellectual environment for the realization of this research. Their commitment to fostering academic inquiry has been instrumental in shaping the trajectory of our work. To the broader academic and scientific community, we acknowledge the wealth of knowledge and advancements in related fields that have paved the way for the integration of interactive 3D models and conventional AI. The collective efforts of researchers worldwide have set the stage for groundbreaking innovations. Lastly, we express our gratitude to our families, friends, and loved ones for their unwavering support, understanding, and encouragement. Their patience and belief in our pursuits have been a source of motivation and inspiration.

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). [3] K. Noda, H. Arie, Y. Suga,and T. Ogata. 2014.Multimodal integration learning of robot using deep neural networks. Elsevier: Robotic and Autonomous Systems. [4] R. Pieraccini, K. Dayanidhi, J. Bloom, J. Dahan, M.l Phillips. 2003. A Multimodal Interface for a Concept Vehicle. Eurospeech 2003. [5] 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. [6] 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 [7] 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 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.