• VeriLook SDK

 

VERILOOK SDK
FACE IDENTIFICATION FOR STAND-ALONE OR WEB APPLICATIONS
VeriLook facial identification technology is designed for biometric systems developers and integrators. The technology assures system performance and reliability with live face detection, simultaneous multiple face recognition and fast face 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, Mac OS X, iOS and Android platforms.

VERILOOK SDK
针对独立系统或WEB应用程序的人脸识别
VeriLook面部识别技术是为生物识别系统开发人员和集成商设计的。该技术保证了系统的性能和可靠性,包括实时人脸检测、同时进行多个人脸识别和在1到1和1到多模式下的快速人脸匹配。
作为一种软件开发工具包,允许在Microsoft Windows、Linux上开发独立和基于Web的解决方案,MacOSX、iOS和Android平台。

 

FEATURES AND CAPABILITIES

  • Millions of algorithm deployments worldwide over the past 15 years.
  • Live face detection prevents cheating with a photo in front of a camera.
  • Simultaneous multiple face processing in live video and still images.
  • Gender classification and age evaluation for each person in an image.
  • Emotion recognition and facial feature points extraction.
  • Webcams or other low cost cameras are suitable for obtaining face images.
  • Near-infrared and visible light spectrum facial images can be matched against each other.
  • Available as multiplatform SDK that supports multiple programming languages.
  • Reasonable prices, flexible licensing and free customer support.

特性和能力

  • 在过去的15年里,全球范围数百万的算法部署
  • 实时人脸检测可以防止在摄像机前使用照片作弊。
  • 在实时视频和静止图像中同时处理多个人脸。
  • 可对图像中每个人进行性别分类和年龄评估。
  • 可进行情感识别与人脸特征点提取。
  • 网络摄像机或其他低成本相机采集的图像均可使用。
  • 近红外和可见光的人脸图像可以相互匹配。
  • 支持多种编程语言的跨平台SDK
  • 合理的价格,灵活的许可和免费的客户支持

 

The VeriLook algorithm implements advanced face localization, enrollment and matching using robust digital image processing algorithms, which are based on deep neural networks:

  • Simultaneous multiple face processing. VeriLook 11.0 performs fast and accurate detection of multiple faces in live video streams and still images. All faces on the current frame are detected in 0.01 - 0.86 seconds depending on selected values for face roll and yaw tolerances, and face detection accuracy. After detection, a set of features is extractedfrom each face into a template in 0.6 seconds. See technical specificationsfor more details.
  • Gender classification. Optionally, gender can be determined for each person on the image with predefined degree of accuracy during the template extraction.
  • Live face detection. A conventional face identification system can be tricked by placing a photo in front of the camera. VeriLook is able to prevent this kind of security breach by determining whether a face in a video stream is "live" or a photograph. The liveness detection can be performed in passive mode, when the engine evaluates certain facial features, and in active mode, when the engine evaluates user's response to perform actions like blinking or head movements. See recommendations for live face detection for more details.
  • Emotions recognition. VeriLook can be configured to recognize emotion type in a human face. Six basic emotions are analyzed: anger, disgust, fear, happiness, sadness and surprise. A confidence value for each of the basic emotions is returned for the face. Larger value for an emotion means that it seems to be more expressed in the face.
  • Facial feature points. The points can be optionally extracted as a set of their coordinates during face template extraction. Each of the 68 points has a fixed sequence number (i.e. number 31 always corresponds to nose tip).
  • Facial attributes. VeriLook can be configured to detect certain attributes during the face extraction – smileopen-mouthclosed-eyesglassesdark-glassesbeard and mustache.
  • Age estimation. VeriLook can optionally estimate person's age by analyzing the detected face in the image.
  • Face image quality determination. A quality threshold can be used during face enrollment to ensure that only the best quality face template will be stored into database.
  • Tolerance to face position. VeriLook allows for 360 degrees of head roll. Head pitch can be up to 15 degrees in each direction from the frontal position. Head yaw can be up to 90 degrees in each direction from the frontal position. See technical specifications for more details.
  • Multiple samples of the same face. Biometric template record can contain multiple face samples belonging to the same person. These samples can be enrolled from different sources and at different times, thus allowing improvement in matching quality. For example a person might be enrolled with and without beard or mustache, etc.
  • Identification capability. VeriLook functions can be used in 1-to-1 matching (verification), as well as 1-to-many mode (identification). The VeriLook 11.0 face template matching algorithm can compare up to 40,000 faces per second on a PC. See technical specifications for more details.
  • Small face features template. A face features template can be as small as 4 Kilobytes, thus VeriLook-based applications can handle large face databases. Also, 5 Kilobytes and 7 Kilobytes templates can be used to increase matching reliability. See technical specifications for more details.
  • Features generalization mode. This mode generates the collection of the generalized face features from several images of the same subject. Then, each face image is processed, features are extracted, and the collections of features are analyzed and combined into a single generalized features collection, which is written to the database. This way, the enrolled feature template is more reliable and the face recognition quality increases considerably.
  • Near-infrared and visible light spectrum face images can be used for face recognition. VeriLook algorithm is able to match faces, which were captured in near-infrared spectrum, against faces, captured in visible light. See the testing results for details.

VeriLook算法利用基于深层神经网络的鲁棒数字图像处理算法实现了高级人脸定位、登录和匹配:

  • 同时进行多面处理。VeriLook 11.0快速准确地检测现场录像流和静止图像,可检测到当前帧上的所有面。根据选择的值的人脸上下和偏转值,以及人脸检测的准确性要求,人脸检测时间在0.01-0.86秒之间。检测之后,一个特征模板提取时间为0.6秒。
  • 性别分类。可选功能,在模板提取过程中,可以预定义的准确度为图像上的每个人确定性别。
  • 现场人脸检测。传统的人脸识别系统可以通过在摄像机前放置一张照片来欺骗。VeriLook能够通过确定视频流中的一张脸是“活体的”还是一张照片来防止这种安全漏洞。活性检测可以在被动模式下执行,由引擎评估某些面部特征时;也可在主动模式下,由引擎评估用户的响应(执行诸如眨眼或头部移动等动作)。
  • 情感识别。VeriLook可以配置为识别人脸中的情感类型。分析了六种基本情绪:愤怒、厌恶、恐惧、快乐、悲伤和惊讶。对面部每一种基本情绪的可信值都会返回给程序,越大的可信值意味着月准确的情绪判断。
  • 面部特征点。在人脸模板提取过程中,可以选择地将点作为一组坐标进行提取。每个68有一个固定的序列号(即数字31总是对应于鼻尖)。
  • 面部特征。可以将VeriLook配置为在人脸提取过程中检测某些属性-微笑张嘴闭上眼睛眼镜墨镜, 和胡须.
  • 年龄估算VeriLook可以通过分析图像中检测到的人脸来选择性地估计人的年龄。
  • 人脸图像质量测定在人脸注册过程中可以使用质量阈值,以确保只将最佳质量的人脸模板存储到数据库中。
  • 对面部位置的容忍度。VeriLook允许360度的头部滚动。头部俯仰可以达到15度在每个方向从正面的位置。头部偏航可以达到90度在每个方向从正面的位置。看见技术规格更多细节。
  • 同一张脸的多个样本。生物识别模板记录可以包含属于同一人的多个人脸样本。这些样品可以从不同的来源和不同的时间登记,从而提高匹配质量。例如,一个人可能注册时有胡子或胡须,等等。
  • 识别能力VeriLook函数可以用于1到1匹配(验证),以及一对多模式(识别)VeriLook11.0人脸模板匹配算法可以在一台PC上以每秒40,000张人脸的速度进行比较。看见技术规格更多细节。
  • 小脸特征模板。人脸特征模板可以小到4千字节,因此基于VeriLook的应用程序可以处理大型人脸数据库。此外,5千字节和7千字节模板可以用来增加匹配的可靠性。看见技术规格更多细节。
  • 特征归一化模式该模式从同一主题的多幅图像中生成广义人脸特征的集合。然后,对每个人脸图像进行处理,提取特征,并将特征集合分析组合成一个单一的广义特征集合,并将其写入数据库。这样,所加入的特征模板更加可靠,人脸识别质量显著提高。
  • 近红外可见光光谱人脸图像可用于人脸识别。VeriLook算法能够匹配在近红外光谱中捕捉到的人脸和在可见光下捕捉到的人脸。。