Human Computer Interaction (HCI) is an emerging technology. Eye gaze technique is one of the very significant techniques of HCI and can be used as hands free pointing tool enabling hands-free operation of the display for the user. The important advantage in using eye gaze systems is that the user can communicate from a distance, and there is no requirement of physical contact with the computer. Investigation of eye gaze helps to understand various aspects of the user like attention, intention, desire and area of interest etc. The eye gaze detection techniques can be classified on the basis of direct eye detection, appearance, template, shape, feature, motion, hybrid, regression, 3D methods etc. There are significant factors like shape and size of the object, distance from the subject, texture, light conditions, colour, orientation, head movement, calibration which may influence and affect the efficiency and effectiveness of the eye gaze detection. The use of the gaze as a human computer interface in different fields is an example of high end applications of these techniques. Eye detection is being used in many real time and interactive high end applications. These include the tracking and analyzing of driver"s behaviour with the head pose detection. It is being used for assessing consumer"s shopping behaviour, pointing and selection, activating commands and combinations with other pointing devices, in surgical and medical applications. Moreover eye gaze techniques are also useful for designing and development of various devices especially for differently abled users.In this paper an extensive research survey has been carried out to understand and analyze the study of various eye gaze techniques, algorithms and models. On the basis of survey of various techniques of eye gaze, a general overview of different phases of eye gaze processing has been presented. Certain technical factors have been identified that are significant and relevant for the working of the models. In the literature survey a number of parameters that are significant for estimation, detection, better efficiency and accuracy of eye gaze techniques have been studied and analysed. A comparison and analytical discussion of different eye gaze techniques and models have been presented. The analysis and classification of the models shall be helpful for further improvement and optimization in the performance and accuracy of eye gaze techniques. General TermHuman computer interaction. KeywordsEye gaze techniques and models, feature based classification and comparison, phases, gaze detection and estimation.
Modification of a digital image by adding or removing some of its elements using a wide variety of image processing tools results in image forgery. As a result authentication of originality of a digital image is becoming a challenging task. Copy-paste forgery is one of the forgeries belonging to context based forgery. Copy-Paste Forgery Detection (CPFD) aims at finding regions that have been copied and pasted within the same or different image. A small change in the image may change statistical parameters that can be analysed for initial assessment of the forgery. In the present research study, a parametric forgery detection model using nonoverlapping block-based technique is developed to ascertain the copy-paste forgery in a given digital image. Statistical parameters of the input image are computed, analysed and compared with those of the forged image. The results show that the proposed model identifies the forged area of the given image and works well with low to moderate copy-paste forgery. The results obtained can be used as the initial verification of the images for forgery and to enhance the forgery detection process by identifying most likely cases of possible image forgeries. The proposed model is tested with large domain of images having different dimensions and for detecting forgery within an image. However, the model has limitations with certain geometrical transformations. General TermsDigital Image Forgery Detection Techniques. KeywordsCopy-paste forgery, Block-based forgery detection techniques, Non-overlapping block-based techniques.
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