WIP20D-GAT40 2.0MP H.265 CCTV Camera
Product Details
WIP20D-GAT40 2.0MP H.265 CCTV Camera
1.1080P HD resolution, clear and fine images;
2.Support 2D/3D noise reduction, digital wide dynamic;
3.Support ONVIF, access third party;
4.Support various mobile monitoring(iPhone, Android);
Datasheet:
Model | WIPD20-GAT40 |
DSP | Hi3516EV100 |
Sensor | 2.0M 1/2.9″ IMX323 low illumination CMOS sensor |
Day/Night | ICR |
Min.Illumination | Low LUX: 0.01LUX @F1.2 (Color) /0.001LUX @F1.2 (B&W) |
Lens | 2.8-12mm HD Manual Zoom |
IR LED | ¢12X6pcs |
IR Distance | 40M |
Noise reduction | Support 2D/3D |
Wide dynamic | Support digital |
Electronic Shutter | 1/50(60) s~ 1/10000s |
Audio (optional) | |
Audio compression | G.711,support bidirectional talk,audio&video synchronization |
Audio interface | 1ch input,level:2Vp-p,impedance:1kΩ,support sound pick-up input |
1ch output,impedance:16Ω,30mw,support microphone | |
Alarm IO (optional) | |
Alarm I/O | 1/0 (support alarm input and video link to background) |
VIDEO | |
Compression | H.265+/H.265X /H.264 |
Image output | Main stream: 1920*1080@20fps,1280*720@25fps; |
Sub-stream: 704*576@25fps; | |
Frame Rate | 1–25FPS ( Adjustable) |
Bit Rate | 100Kpbs~8Mpbs(Adjustable) |
NETWORK | |
Protocol | RTSP/FTP/PPPOE/DHCP/DDNS/NTP/UPnP etc. |
ONVIF | Support |
Other function | Support WEB,OSD,live video transmission, motion detect and IO alarm, front-end storage/playback/download, and center
reminder and image linkage, support JPEG capture; united remote client monitoring software, MYEYE,perfect SDK; |
PC Client & Browser | CMS/VMS, IE |
Mobile Phone | iPhone,iPad,Android Mobile(‘XMeye’ app) |
INTERFACE | |
Video Output | RJ45 |
LAN | 1 RJ45 10/100 Ethernet port |
GENERAL | |
Working Temperature | -10 C ~ + 50 C |
Working Humidity | 0% ~ 90% |
Power Supply | DC12V/POE (optional), 2.0A |
Dimension | 249(L)×80(W)×82(D)mm |
Weight | 1.4Kg |
Package | 16pcs/carton (59×34.5×48.5cm) |
FAQ:
Why Face recognition becomes the commanding point technology of video surveillance?
In the era of big data explosion, update iteration is the constant theme in the kaleidoscopic changes. Only walking ahead of the current situation can lead the future. In 2017, the hottest and most popular technology and product in video surveillance should be face recognition. All major CCTV manufacturers have launched various powerful face recognition systems. Especially, put forward the concept of “deep learning”.
Firstly, the traditional face recognition (a generation of learning methods are shallow learning) identification accuracy can up to 70%, even after deployment of security personnel time attention should be paid.However, the face recognition system with deep learning technology can achieve an average accuracy of more than 90% in all days, which can greatly save the energy of security personnel after deployment.
Secondly, Traditional face recognition can only be recognized by simple attributes such as binocular features, and the recognizable face attributes are too few. The face recognition system using the deep learning technology adopts the global face feature retrieval to model the global features of the face, not limited to the local characteristics of the human eye, so the accuracy of the depth learning face recognition algorithm has exceeded the human eye limit.
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