Context-Based Algorithm for Face Detection
Independent thesis Advanced level (degree of Magister), 20 points / 30 hpStudent thesis
Face detection has been a research area for more than ten years. It is a complex problem due to the high variability in faces and amongst faces; therefore it is not possible to extract a general pattern to be used for detection. This is what makes the face detection problem a challenge.
This thesis gives the reader a background to the face detection problem, where the two main approaches of the problem are described. A face detection algorithm is implemented using a context-based method in combination with an evolving neural network. The algorithm consists of two majors steps: detect possible face areas and within these areas detect faces. This method makes it possible to reduce the search space.
The performance of the algorithm is evaluated and analysed. There are several parameters that affect the performance; the feature extraction method, the classifier and the images used.
This work resulted in a face detection algorithm and the performance of the algorithm is evaluated and analysed. The analysis of the problems that occurred has provided a deeper understanding for the complexity of the face detection problem.
Place, publisher, year, edition, pages
Institutionen för teknik och naturvetenskap , 2005. , 45 p.
Face detection, image processing, neural networks, feature extraction
IdentifiersURN: urn:nbn:se:liu:diva-4171ISRN: LITH-ITN-MT-EX--05/052--SEOAI: oai:DiVA.org:liu-4171DiVA: diva2:20552