CAM-C1126S2U Intelligent Dual-Lens Camera Module

Equipped with high-performance quad-core AI intelligent vision processor with computing power up to 2.0Tops, the module supports 4K video coding and decoding, various AI frameworks and human detection with high recognition accuracy — it is suitable for face recognition, gate access control, gesture recognition, expression recognition, face attribute analysis, etc. Abundant resources facilitate secondary development and help the project to be implemented quickly.

Quad-core AI vision processor

Low-consumption AI vision processor RV1126, with 14nm lithography process and quad-core 32-bit ARM Cortex-A7 architecture, integrates NEON and FPU — the frequency is up to 1.5GHz. It supports FastBoot, TrustZone technology and multiple crypto engines.

Various AI frameworks

Built-in neural network processor NPU with computing power up to 2.0 Tops realizes that the power consumption of AI computing is less than 10% of the power required by the GPU. With tools and supporting AI algorithms provided, it supports direct conversion and deployment of Tensorflow, PyTorch, Caffe, MxNet, DarkNet, ONNX, etc.

HDR+ WDR dual-lens

With built-in 3F-HDR ISP, multi-level noise reduction, 3F-HDR, and other technologies, it is equipped with dual-lens 2M (RGB+IR) WDR camera; it not only meets the scenes of strong light, backlight and darknessVarious AI frameworks, but also realizes human detection and anti-spoofing functions of face recognition.

Efficient recognition, high accuracy

It supports face database up to 100,000 capacity; it has efficient recognition speed, and identifies the target quickly — the recognition accuracy rate is 99.7%.

4K H.265 encoding & decoding

Built-in Video CODEC supports 4K H.254/H.265@30FPS and multi-channel video encoding and decoding, meeting the needs of low bit rate, low-latency encoding, perceptual encoding and making the video occupancy smaller.

Master & slave integration

It can be used as a USB device to output visual processing data and images to the computer; or can be used as an IPCAM monitoring and identification front end to connect to the NVR through the network port; and also can be connected to a 1080P screen through MIPI to make a face recognition or an AI vision terminal.

Small size, easy to integrate

Equipped with all-aluminum alloy shell, the space-saving module has efficient heat dissipation and can be flexibly embedded in various AI products.

Abundant resources for customization

A complete SDK, including cross compiler toolchain, BSP source code, application development environment, development documents, examples and other resources, is provided for the users to make a further customization.

Applications

It is widely used in face recognition, gesture recognition, gate access control, smart security, smart IP camera, smart doorbell/peephole, self-service terminals, smart finance, smart construction, smart travel and other industries.

face recognition

gesture recognition

gate access control

self-service terminals

smart finance

smart construction

Specification

	CAM-C1109S2U	CAM-C1126S2U
SoC	RV1109	RV1126
CPU	Dual-core ARM Cortex-A7 32-bit , frequency 1.5GHz, integrate NEON and FPU Each core has a 32KB I-cache, 32KB D-cache and 512KB shared second-level cache Based on RISC-V MCU	Quad-core ARM Cortex-A7 32-bit, frequency 1.5GHz, integrate NEON and FPU Each core has a 32KB I-cache, 32KB D-cache and 512KB shared second-level cache Based on RISC-V MCU
NPU	1.2Tops, support INT8/ INT16, It has strong network model compatibility and provides RKNN tool, which can realize the conversion of commonly used AI framework models Eg: (caffe, darknet, mxnet, onnx, pytorch, tensorflow, tflite) and algorithm support	Computing power up to 2.0Tops, supports INT8/ INT16, It has strong network model compatibility and provides RKNN tool, which can realize the conversion of commonly used AI framework models Eg: (caffe, darknet, mxnet, onnx, pytorch, tensorflow, tflite) and algorithm support
RAM	1GB / 2GB DDR3	1GB / 2GB DDR4
Storage	8GB / 16GB eMMC	8GB / 16GB eMMC
Video Encoding	H.264/H.265 encoding capability: 2688 x 1520@30 fps+1280 x 720@30 fps 3072 x 1728@30 fps+1280 x 720@30 fps 2688 x 1944@30 fps+1280 x 720@30fps	4K H.264/H.265 30fps video encoding: 3840 x 2160@30 fps+720p@30 fps encoding
Video Decoding	5M H.264/H.265 decoding	4K H.264/H.265 30fps video decoding 3840 x 2160@30 + 3840 x 2160@30 fps decoding
OS	Linux	Linux
Power	5V	5V
Operating Temperature	-10℃～60℃	-10℃～60℃
Operating Humidity	10%～90 %	10%～90 %
Dual-Lens Camera
	Camera (IR)	Camera (RGB)
Dual-Lens Camera	GC2053	GC2093
Sensor Size	1 / 2.9	1 / 2.9
Resolution	1920*1080	1920*1080
Pixel Size	2.8 μm	2.8 μm
Output Format	RAW	RAW
Interface	MIPI	MIPI
Focus Distance	80 cm	80 cm
Lens	4P	4P
Filter	850 nm	650 nm
Field Angle	D70°H62°V38°	D70°H62°V38°
Distortion	≤0.5%	≤0.5%
Aperture/ Focal Length	F2.0/4.3mm	F2.0/4.3mm
Resolving Power	Center: 800 Around: 600	Center: 800 Around: 600
Face Recognition & Detection
Max Database	100,000
Recommended Database	10,000
Accuracy	Under standard test environment, 10,000 database No Mask: Accuracy 99% With mask: Accuracy 95%
Face Detection	Face detection time: ~23ms Face tracking time: ~7ms
Human Detection	Single-lens detection time: ~45ms Dual-lens detection time: ~15ms
Face Recognition	Feature extraction time: ~25ms Single recognition time: ~0.0115ms
Recommended Image Input Size	720P
Min Face Recognition Size	5050 pixel (Non-human) 9090 pixel (Human)
Recommended Face Recognition Angle	Yaw ≤ ±30° Pitch ≤ ±30° Roll≤ ±30°
Appearance
Dimension	84.0mm × 22.45mm × 19.35mm
Shell	All aluminum alloy design, efficient heat dissipation

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