AI Facial Recognition for Haunted Attractions
Budget: $25 – $50 USD
Haunted Attraction Special Effects System
Project Overview:
We are seeking a software engineer to develop a custom interactive software system for a haunted attraction. The system will use motion detection, face recognition, and AI-powered image manipulation to create a unique special effect. The goal is to capture a patron’s face, morph it into a ghostly or monstrous appearance, embed it into a pre-existing video, and play the video back on a hidden TV in real-time when triggered. This system must operate smoothly to ensure seamless operation without causing delays in crowd throughput.
Project Scope:
1. Hardware Integration:
• Raspberry Pi 5 as the primary controller.
• Hailo AI HAT with 13 TOPS for image processing and AI tasks.
• Night vision Raspberry Pi camera for face capture in low-light conditions.
• Motion sensors or pressure mats to trigger the system.
• HDMI output to display the final video on a TV.
2. Software Requirements:
• Motion Detection and Triggering: Use motion detection or pressure mat input to activate the system.
• Face Detection and Recognition: Capture the patron’s face in real-time and identify the region for manipulation.
• Image Morphing: Apply various effects (ghost, zombie, melting face, etc.) to the captured face using AI.
• Video Embedding: Insert the manipulated face into a pre-existing video template.
• Playback: Play the final video on the connected TV seamlessly after processing.
• Effect Rotation: Rotate between different effects and video templates for variety.
3. Performance Requirements:
• Real-time or near real-time processing (under 5 seconds).
• Ability to handle multiple patrons without bottlenecks.
• Lightweight software to optimize performance on Raspberry Pi.
4. Customization and Scalability:
• Include options for adding new effects or videos in the future.
• Easy-to-use interface or configuration file for non-technical operators to modify settings (e.g., duration, effect selection, trigger sensitivity).
5. Flow Optimization Features:
• Time-limited playback to prevent patrons from lingering.
• Default loop video displayed on the TV when not triggered.
• Support for parallel systems to manage higher traffic.
6. Additional Features (Optional):
• Log or track the number of activations for operational insights.
• Remote monitoring and control capabilities.
• Audio integration to add sound effects synced with the video.
Deliverables:
1. Fully functional software that integrates all specified features.
2. Detailed installation and setup guide, including dependencies and configuration instructions.
3. Basic user manual for operation and troubleshooting.
4. Source code with comments for future modifications.
Preferred Skills and Experience:
• Experience with Raspberry Pi development (especially Raspberry Pi 5).
• Proficiency in Python, OpenCV, and AI/ML frameworks (e.g., TensorFlow, PyTorch).
• Familiarity with video editing libraries like FFmpeg or OpenCProject Brief for Software Engineer
• Expertise in real-time image and video processing.
• Knowledge of integrating sensors (motion detection, pressure mats) with Raspberry Pi GPIO.
Timeline:
• Initial prototype: 2 weeks
• Final delivery: 3 weeks
Budget: Please provide an estimated quote for the project, including post-delivery support if needed.
We look forward to your proposal! Let us know if you need any additional details.
Project Overview:
We are seeking a software engineer to develop a custom interactive software system for a haunted attraction. The system will use motion detection, face recognition, and AI-powered image manipulation to create a unique special effect. The goal is to capture a patron’s face, morph it into a ghostly or monstrous appearance, embed it into a pre-existing video, and play the video back on a hidden TV in real-time when triggered. This system must operate smoothly to ensure seamless operation without causing delays in crowd throughput.
Project Scope:
1. Hardware Integration:
• Raspberry Pi 5 as the primary controller.
• Hailo AI HAT with 13 TOPS for image processing and AI tasks.
• Night vision Raspberry Pi camera for face capture in low-light conditions.
• Motion sensors or pressure mats to trigger the system.
• HDMI output to display the final video on a TV.
2. Software Requirements:
• Motion Detection and Triggering: Use motion detection or pressure mat input to activate the system.
• Face Detection and Recognition: Capture the patron’s face in real-time and identify the region for manipulation.
• Image Morphing: Apply various effects (ghost, zombie, melting face, etc.) to the captured face using AI.
• Video Embedding: Insert the manipulated face into a pre-existing video template.
• Playback: Play the final video on the connected TV seamlessly after processing.
• Effect Rotation: Rotate between different effects and video templates for variety.
3. Performance Requirements:
• Real-time or near real-time processing (under 5 seconds).
• Ability to handle multiple patrons without bottlenecks.
• Lightweight software to optimize performance on Raspberry Pi.
4. Customization and Scalability:
• Include options for adding new effects or videos in the future.
• Easy-to-use interface or configuration file for non-technical operators to modify settings (e.g., duration, effect selection, trigger sensitivity).
5. Flow Optimization Features:
• Time-limited playback to prevent patrons from lingering.
• Default loop video displayed on the TV when not triggered.
• Support for parallel systems to manage higher traffic.
6. Additional Features (Optional):
• Log or track the number of activations for operational insights.
• Remote monitoring and control capabilities.
• Audio integration to add sound effects synced with the video.
Deliverables:
1. Fully functional software that integrates all specified features.
2. Detailed installation and setup guide, including dependencies and configuration instructions.
3. Basic user manual for operation and troubleshooting.
4. Source code with comments for future modifications.
Preferred Skills and Experience:
• Experience with Raspberry Pi development (especially Raspberry Pi 5).
• Proficiency in Python, OpenCV, and AI/ML frameworks (e.g., TensorFlow, PyTorch).
• Familiarity with video editing libraries like FFmpeg or OpenCProject Brief for Software Engineer
• Expertise in real-time image and video processing.
• Knowledge of integrating sensors (motion detection, pressure mats) with Raspberry Pi GPIO.
Timeline:
• Initial prototype: 2 weeks
• Final delivery: 3 weeks
Budget: Please provide an estimated quote for the project, including post-delivery support if needed.
We look forward to your proposal! Let us know if you need any additional details.