Sign In | Join Free | My infospaceinc.com
infospaceinc.com
Products
 Search by Category
Home >

Binocular Face Recognition 3D Stereo Vision Camera Module

Binocular Face Recognition 3D Stereo Vision Camera Module

Binocular Face Recognition 3D Stereo Vision Camera Module
Binocular Face Recognition 3D Stereo Vision Camera Module
Categories Face Recognition Camera Module
Storage: 8GB/16GB eMMC
Power: 5V/1A
Output Format: Camera（IR）: RAW Camera（RGB）: RAW
Recommended Database: 10,000
Module Size: 84.0mm × 22.45mm × 19.35mm
Processor: Quad-core ARM Cortex-A7 32-bit, 1.5GHz, with integrated NEON and FPU Each core has a 32KB I-cache and 32KB D-cache, plus 512KB shared L2 cache Based on RISC-V MCU
Interface: Camera（IR）: MIPI Camera（RGB）: MIPI
Maximum Database: 100,000
Recommended Face Recognition Angles: Yaw: ≤ ±30° Pitch: ≤ ±30° Roll: ≤ ±30°
Face Comparison: Feature Extraction Time: ~25 ms Single Comparison Time: ~0.0115 ms
Video decoding: 4KH.264/H.26530fps 3840x2160@30encoding+3840x2160@30fpsdecoding
Image Sensors: Camera（IR）: GC2053 Camera（RGB）: GC2093
Pixel Size: Camera（IR）: 2.8 μm Camera（RGB）: 2.8 μm
Recommended Image: 720P
Video encoding: 4KH.264/H.26530fps 3840x2160@30fps+720p@30fpsencoding
Sensor Size: Camera（IR）: 1 / 2.9 Camera（RGB）: 1 / 2.9
System support: Linux
Operating humidity: 10%～90%
Resolution: Camera（IR）: Center 800 Edge 600 Camera（RGB）: Center 800 Edge 600
Face Recognition Accuracy: Standard Testing Environment, 10,000-person Database: Without Mask: False Acceptance Rate: 0.01%; Recognition Accuracy: 99% With Mask: False Acceptance Rate: 0.01%; Recognition Accuracy: 95%
Enclosure Design: Aluminum alloy material with serrated heat sink back cover for efficient cooling
Lens: Camera（IR）: 4P Camera（RGB）: 4P
Liveness Detection: Monocular Liveness Detection Time: ~45 ms Binocular Liveness Detection Time: ~15 ms
NPU: Up to 2.0 Tops performance, supports INT8/INT16, strong network model compatibility, RKNN model conversion tool available for converting common AI framework models (e.g., Caffe, Darknet, MXNet, ONNX, PyTorch, TensorFlow, TFLite) and algorithm support
Face Detection: Face Detection Time: ~23 ms Face Tracking Time: ~7 ms
Memory: 1GB/2GBDDR4
Filter Wavelength: Camera（IR）: 850 nm Camera（RGB）: 650 nm
Payment Terms: T/T
Optical Distortion: Camera（IR）: ≤0.5% Camera（RGB）: ≤0.5%
Focal Length: Camera（IR）: F2.0/4.3mm Camera（RGB）: F2.0/4.3mm
Host computer chip: RV1126
Focusing Distance: Camera（IR）: 80 cm Camera（RGB）: 80 cm
Model Number: JP1126
Place of Origin: China
MOQ: Negotiable
Price: Negotiable
Supply Ability: 200+/day
Delivery Time: 5-8 work days
Operating temperature: -10℃～60℃
Power Consumption: Typical Power Consumption: 2.8W (5V, 560mA) Maximum Power Consumption: 4.3W (5V, 860mA) Minimum Power Consumption: 0.71W (5V, 142mA) Power Supply Recommendation: 5V/1.2A or higher
Field of View: Camera（IR）: D70°H62°V38° Camera（RGB）: D70°H62°V38°
Minimum Face Size for Recognition: Without Liveness Detection: 50 x 50 pixels With Liveness Detection: 90 x 90 pixels）
Contact Now
Company Info.
Shenzhen Jupin Technology Co., Ltd.
View Contact Details
Product List
  • Haven't found right suppliers
  • Our buyer assistants can help you find the most suitable, 100% reliable suppliers from China.
  • And this service is free of charge.
  • we have buyer assistants who speak English, French, Spanish......and we are ready to help you anytime!
Submit Buying Request
  • Product Details
  • Company Profile

Binocular Face Recognition 3D Stereo Vision Camera Module

JP1126 Intelligent Dual-Lens Camera Module Up to 2.0 Tops performance, supports INT8/INT16 5V/1A


JP1126 Intelligent Dual-Lens Camera Module Features:

  1. High-performance AI intelligent vision processor
  2. Powerful AI computing capabilities
  3. Wide dynamic range dual-lens camera
  4. AI vision system with integrated master-slave functionality
  5. Robust video encoding and decoding capabilities
  6. Compact design
  7. Open-source documentation
  8. Extensive application scenarios
  9. Equipped with a 2MP RGB+IR infrared dual-lens camera module, supporting liveness detection to effectively prevent spoofing using photos, videos, or wax figures.
  10. Ensures accurate facial recognition even in complex and extreme lighting conditions.
  11. Widely applicable to facial recognition, gesture recognition, access control systems, smart finance, smart construction sites, smart transportation, and more.By adopting this camera module solution, you can achieve fast and low-barrier implementation of facial recognition terminal products.

JP1126 Intelligent Dual-Lens Camera Module Parameter:

Processor:
Quad-core ARM Cortex-A7 32-bit, 1.5GHz, with integrated NEON and FPU
Each core has a 32KB I-cache and 32KB D-cache, plus 512KB shared L2 cache
Based on RISC-V MCU
NPU:
Up to 2.0 Tops performance, supports INT8/INT16, strong network model compatibility,
RKNN model conversion tool available for converting common AI framework models (e.g.,
Caffe, Darknet, MXNet, ONNX, PyTorch, TensorFlow, TFLite) and algorithm support
Memory:
1GB/2GBDDR4
Storage:
8GB/16GB eMMC
Video encoding:
4KH.264/H.26530fps
3840x2160@30fps+720p@30fpsencoding
Video Decoding:
4KH.264/H.26530fps
3840x2160@30encoding+3840x2160@30fpsdecoding
System support:
Linux
Power:
5V/1A
Image Sensors:
GC2053
GC2093
Module Board Dimensions:80* 16* 17.6mm (L* W* H)
Resolution:
1920*1080
Pixel Size:
2.8 μm
Interface:
MIPI
Focal Length:
F2.0/4.3mm
Maximum Database:
100,000
Face Recognition
Accuracy:
Standard Testing Environment, 10,000-person Database:
Without Mask:
False Acceptance Rate: 0.01%; Recognition Accuracy: 99%
With Mask:
False Acceptance Rate: 0.01%; Recognition Accuracy: 95%


Product Tags:

HD Face Recognition Module

  

Face Recognition Module DC5V

  

1920x1080 face detection module

  
Buy Binocular Face Recognition 3D Stereo Vision Camera Module at wholesale prices

Binocular Face Recognition 3D Stereo Vision Camera Module

Send your message to this supplier
 
*From:
*To: Shenzhen Jupin Technology Co., Ltd.
*Subject:
*Message:
Characters Remaining: (0/3000)
 
You May Like
Inquiry Cart 0