Robust Finger Tracking with Multiple Cameras
RATFG-RTS '99 Proceedings of the International Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Face Recognition Using IPCA-ICA Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human hand recognition using IPCA-ICA algorithm
EURASIP Journal on Applied Signal Processing
CBIR approach to the recognition of a sign language alphabet
CompSysTech '07 Proceedings of the 2007 international conference on Computer systems and technologies
An introduction to biometric recognition
IEEE Transactions on Circuits and Systems for Video Technology
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This paper presents a heuristic approach to 3D object recognition by considering multiple 2D projections (appearances) of the objects of interest. Thus, 3D object identification is interpreted as a conventional Content Based Image Retrieval (CBIR) problem. An arbitrary input image of a given object is treated as a search sample within a database (DB) of a large enough set of images, i.e. appearances from a sufficient number of viewpoints for each object. The CBIR method to access the image DB should be both fast enough and sufficiently noise-tolerant. The method we propose is described over two cases of recognition, namely human faces and hand signs of a given sign-language alphabet. Analogically, the method can also be applied to recognition of a large number of 3D objects of different types. We are briefly covering the data gathering technique, its structuring into a DB of image samples, and the experimental study for the noise-resistance of the applied CBIR method. The latter is used to acknowledge the applicability of the proposed approach.