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Highly Optimized Algorithm for Face Detection and Classification

Developer:  Synesis  |  all projects

There is a number of applications designed for rapid face detection and analysis of still images and live video including but not limited to: ??? Rapid analysis of huge image data sets to classify whether the image contains human faces or not, how many of them there are, what visibility parameters are, etc. It is mainly used with Internet search engines to extend the parameter vector and to produce more relevant search results; ??? Analysis of human attention to any object (i.e. an advertisement billboard) by means of a camera installed and detecting people paying attention to the object under analysis which provides accurate analysis of actual foot traffic and attention time distribution; ??? Security and surveillance applications for detection of people within a live CCTV video stream, extraction of high-resolution face images, pre-selection of best images to be passed along for further face recognition systems. A face detector performs search for all human faces of a specified image and for each image it provides a range of parameters which are later used by Portrait Classifier for rank calculation. Portrait Classifier being a subsequent stage in the processing sorts out images into specified types such as Person Portrait, Multi-person portrait and Not-A-Human Photo. For each image its rank is also calculated which is an additional parameter for Internet image search engine along with common indices (citations, popularity, etc). The designed algorithm is of high performance and scalability ensuring 1.83 MB/sec of image data processing on Core2Duo CPU.

Target area

Programming languages: C, C++

Technologies: Intel x86 MMX instruction set optimization

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