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Your search keyword '"Habib, Hafiz Adnan"' showing total 22 results
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22 results on '"Habib, Hafiz Adnan"'

8. Infotainment devices control by eye gaze and gesture recognition fusion

Author

Nawaz, Tabassam, Mian, Muhammad Saleem, and Habib, Hafiz Adnan

Subjects
Algorithms -- Usage, Machine vision -- Research, Real-time control -- Design and construction, Real-time systems -- Design and construction, Algorithm, Real-time system, Business, Electronics and electrical industries, Engineering and manufacturing industries
Abstract

This paper presents a novel concept for controlling the consumer devices such as MP3 player or other daily life appliances by fusion of eye gaze and gesture recognition methodologies. Such system is deployable for virtually controlling the consumer devices anywhere in the home and office. The usability of the system is also tested with patients at the intensive care units of the hospitals where the patients may not able to operate the consumer devices in a regular way. The proposed system consists of a video processing based embedded system, a CCD camera and situated display. Physical control options are displayed over the situated display. Selection/de-selection process of displayed control option over situated display is accomplished by analyzing the video sequence captured by the CCD camera. Eye gaze estimation and head gesture recognition algorithms analyze the video sequence and reveal the control command that has to be sent to the infotainment or other consumer devices. Index Terms--virtual consumer appliance control, gesture recognition, gaze direction estimation, recognition fusion, real time vision system.

Published
2008

9. Real time mono vision gesture based virtual keyboard system

Author

Habib, Hafiz Adnan and Mufti, Muid

Subjects
Keyboards (Electronics) -- Models, Keyboards (Electronics) -- Research, Real-time control -- Research, Real-time systems -- Research, Virtual computer systems -- Research, Virtual computer systems -- Models, Keyboard, Keyboard accessory, Real-time system, Business, Electronics and electrical industries, Engineering and manufacturing industries
Abstract

This paper presents a novel mono-vision virtual keyboard design for consumers of mobile and portable computing devices such as PDA's, mobile phones etc. Fuzzy approaches to gesture recognition are developed to reveal the key pressed over the printed sheet keyboard by analyzing the hand and finger gesture captured in the video sequence. Real time system is developed by integrating SDIO camera with PDA in the application environment. Reliable results are experienced by the implementation of the proposed real time mono vision gestured virtual keyboard system. Index Terms--mono vision virtual keyboard, fuzzy gesture, real time consumer gesture system, hand trajectory representations.

Published
2006

10. A robust technique for copy-move forgery detection from small and extremely smooth tampered regions based on the DHE-SURF features and mDBSCAN clustering.

Author

Bilal, Muhammad, Habib, Hafiz Adnan, Mehmood, Zahid, Yousaf, Rehan Mehmood, Saba, Tanzila, and Rehman, Amjad

Subjects
*FORGERY, *EUCLIDEAN distance, *IMAGE registration, *OCEAN waves
Abstract

The keypoint-based copy-move forgery (CMF) detection is one of the most widely used CMF detection methods; however the keypoint-based CMF detection method cannot effectively and efficiently detect the small and extremely smooth tampered regions in the input image. A CMF detection method is proposed to tackle the above mention problem. In the proposed CMF detection method, the contrast of the input image is adjusted using the dynamic histogram equalization (DHE) method. A speeded-up robust feature (SURF) descriptor is used to extract features from the tampered image and matched using Euclidean distance. The novel modified density-based spatial clustering of application with noise (mDBSCAN) clustering technique is applied to the matched features to generate the binary mask followed by the detection of CMF regions. Three standard datasets, MICC-F220, MICC-F2000, and CoMoFoD, are used to evaluate the proposed CMF detection method performance. The experimental results indicate that the proposed CMF detection method outshines the state-of-the-art CMF detection method in terms of precision (P) and recall (R). [ABSTRACT FROM AUTHOR]

Published
2021
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