優異的演算法與強大能力

可以在PC、行動裝置上發揮同樣可靠的辨識精度。能同時處理同一影格內多個人臉的資訊，包括活人臉部偵測、性別分類、擷取面部特徵等等。

SentiVeillance SDK 軟體開發包

SentiVeillance Standard SDK適合線下獨立運作的研發，Extended SDK適合連上網際生物資料庫系統的研發者。SDK內含的裝置管理軟體，讓使用者可同時監控多台攝影機，並在其架構上製作支援額外裝置之plug-in。

技術細節

SentiVeillance在PC上每秒最大可配對40,000張臉部資料，可在0.6秒內特定出對象，在資料庫中每筆臉部資料可小達4KB。

System requirements 
• PC or server with a compatible processor: 
     • 3 GHz or better processor with 6 processor cores is recommended. 
     • AVX2 support is highly recommended. Processors that do not support AVX2 will still run the SentiVeillance algorithms, but in a mode, which will not provide the specified performance. Most modern processors support this instruction set, but please check if a particular processor model supports it. 
• A graphical processing unit (GPU): 
     • a GPU is required if a SentiVeillance component with any of the supported modalities is run to process more than 2 video streams simultaneously. 
     • NVIDIA GeForce GTX 1080 GPU or better is recommended to process up to 10 video streams on a node. 
     • Several GPUs can be used on the same machine to process larger number of video streams. 
     • at least 6 GB of VRAM is recommended. 
     • Compute Capability 3.5 or better should be supported by the GPU. 
     • CUDA 11.2 toolkit or newer is required 
     • cuDNN 7.5 library is required. 
     • At least 8 GB of RAM.
     • A high-resolution digital camera. The camera resolution may vary depending on the actual application. The recommended resolution is about 2 MegaPixel, as processing video from cameras with higher resolution will require more free RAM and more powerful processor to keep the acceptable frame rate. These supported cameras are suitable for using with SentiVeillance SDK: 
     • Any IP camera, that supports RTSP (Real Time Streaming Protocol):
         • Only RTP over UDP is supported.      
         • VLC framework can be optionally used for reading video streams.
         • H.264/MPEG-4 AVC or Motion JPEG should be used for encoding the video stream. 
     • Any high-resolution digital camera that is accessible using: 
         • DirectShow or Windows Media or Media Foundation interfaces for Microsoft Windows platform; 
         • GStreamer interface for Linux platform. 
     • Any other device support can be added by customers using the provided Device Manager Plug-in Framework.

Microsoft Windows specific requirements 
     • Microsoft Windows 7 / 8 / 10 / Server 2008 / Server 2008 R2 / Server 2012, 64-bit. 
     • Microsoft .NET framework 4.5 or newer (for .NET components usage). 
     • Microsoft DirectX 9.0 or later. 
     • One of following development environments for application development: 
     • Microsoft Visual Studio 2012 or newer (for application development under C/C++, C#, Visual Basic .Net)
     • Java SE JDK 8 or newer 

Linux specific requirements 
     • Ubuntu 20.04 OS 
     • glibc 2.17 or newer 
     • GStreamer 1.10.x or newer with gst-vaapi plugins installed for hardware accelerated video decoding 
     • libgudev-1.0 219 or newer 
     • wxWidgets 3.0.0 or newer libs and dev packages (to build and run SDK samples and applications based on them) 
     • Java SE JDK 8 or newer (for application development with Java) 

Linux specific Virtual machine (VM) requirements 
     •  VM must be connected to the network in bridge mode, so that UDP packets from camera can reach the VM. 
     • The default vaapi plugin must be removed, because it's buggy and taking priority even when it can't function under MVs:
        apt-get remove gstreamer1.0-vaapi 
     • h264 codec must be installed
        apt-get install gstreamer1.0-libav

MegaMatcher SDK

MegaMatcher is designed for large-scale AFIS and multi-biometric systems developers. The technology ensures high reliability and speed of biometric identification even when using large databases.

Available as a software development kit that allows development of large-scale single- or multi-biometric fingerprint, iris, face, voice or palm print identification products for Microsoft Windows, Linux, macOS, iOS and Android platforms.

MegaMatcher Accelerator

MegaMatcher Accelerator is a hardware/software solution that provides high speed, high volume biometric identification for national-scale projects.

The Extreme and Extended versions are designed to run on server hardware and perform fast biometric template matching on the server-side of a large-scale AFIS or multi-modal system. The Standard version and Development Edition are intended to be run on a common PC.

MegaMatcher On Card SDK

MegaMatcher On Card SDK offers matching-on-card technology that stores a person's fingerprint, iris and face templates on a smart card and performs template matching in a microprocessor embedded in the card, instead of matching biometric information on a PC processor.

The match-on-card method ensures that personal biometric information does not transfer to an external computer as it would in a more basic template-on-card system.

VeriFinger SDK

VeriFinger is a fingerprint identification technology designed for biometric systems developers and integrators. The technology assures system performance with fast, reliable fingerprint matching in 1-to-1 and 1-to-many modes.

Available as a software development kit that allows development of stand-alone and Web-based solutions on Microsoft Windows, Linux, macOS, iOS and Android platforms.

VeriEye SDK

VeriEye iris identification technology is designed for biometric systems developers and integrators. The technology includes many proprietary solutions that enable robust iris enrollment under various conditions and fast iris matching in 1-to-1 and 1-to-many modes.

Available as a software development kit that allows development of stand-alone and Web-based solutions on Microsoft Windows, Linux, macOS, iOS and Android platforms.

VeriSpeak SDK

VeriSpeak voice identification technology is designed for biometric system developers and integrators. The text-dependent speaker recognition algorithm assures system security by checking both voice and phrase authenticity. Voiceprint templates can be matched in 1-to-1 (verification) and 1-to-many (identification) modes.

Available as a software development kit that enables the development of stand-alone and Web-based speaker recognition applications on Microsoft Windows, Linux, macOS, iOS and Android platforms.

Sentigaze SDK

SentiGaze is designed for developers who want to use computer vision-based gaze tracking in their applications. The technology works with webcam and common PC. Usage convenience is ensured by contactless gaze tracking and calibration to specific screen size and user position.

Available as a software development kit that provides for the development of gaze tracking systems for Microsoft Windows.

SentiSculpt SDK

SentiSculpt is designed for software developers who want to use computer vision-based 3D object model reconstruction from images in their applications.

Object models are created automatically from sets of photos, which were captured from different angles using regular cameras.