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Sample Thesis Title with a Concise and Accurate ON EFFECTIVE HUMAN-ROBOT INTERACTION BASED ON RECOGNITION AND ASSOCIATION DISSERTATION Submitted by Avinash Kumar Singh In Partial Fulfillment of the Requirements For the Degree of DOCTOR OF PHILOSOPHY Under the Supervision of PROF. G.C. NANDI DEPARTMENT OF INFORMATION TECHNOLOGY भारतीय सचू ना प्रौद्योगिकी संथान INDIAN INSTITUTE OF INFORMATION TECHNOLOGY, ALLAHABAD (A centre of excellence in IT, estaइलाहाबादblished by M inistry of HRD, Govt. of India) 12 February 2016 INDIAN INSTITUTE OF INFORMATION TECHNOLOGY ALLAHABAD (A Centre of Excellence in Information Technology Established by Govt. of India) CANDIDATE DECLARATION I, Avinash Kumar Singh, Roll No. RS-110 certify that this thesis work entitled “On Effective Human - Robot Interaction based on Recognition and Association” is submitted by me in partial fulfillment of the requirement of the Degree of Doctor of Philosophy in Department of Information Technology, Indian Institute of Information Technology, Allahabad. I understand that plagiarism includes: 1. Reproducing someone else's work (fully or partially) or ideas and claiming it as one's own. 2. Reproducing someone else's work (Verbatim copying or paraphrasing) without crediting 3. Committing literary theft (copying some unique literary construct). I have given due credit to the original authors/ sources through proper citation for all the words, ideas, diagrams, graphics, computer programs, experiments, results, websites, that are not my original contribution. I have used quotation marks to identify verbatim sentences and given credit to the original authors/sources. I affirm that no portion of my work is plagiarized. In the event of a complaint of plagiarism, I shall be fully responsible. I understand that my Supervisor may not be in a position to verify that this work is not plagiarized. Name: Avinash Kumar Singh Date: 12/02/16 Enrolment No: RS-110 Department of Information Technology, IIIT-Allahabad (U.P.) ii Robotics and Artificial Intelligence Laboratory, Indian Institute of Information Technology Allahabad, India INDIAN INSTITUTE OF INFORMATION TECHNOLOGY ALLAHABAD (A Centre of Excellence in Information Technology Established by Govt. of India) CERTIFICATE FROM SUPERVISOR I do hereby recommend that the thesis work done under my supervision by Mr. Avinash Kumar Singh (RS 110) entitled “On Effective Human- Robot Interaction based on Recognition and Association” be accepted in partial fulfillment of the requirement for the Degree of Doctor of Philosophy in Department of Information Technology, Indian Institute of Information Technology, Allahabad. Prof. G.C. Nandi Supervisor, IIIT-Allahabad iii Robotics and Artificial Intelligence Laboratory, Indian Institute of Information Technology Allahabad, India Keywords ….Identification of persons ........Human-robot Interaction …………Human perception based criminal identification …………Robot sketch drawing …………Face biometric based criminal identification …………Anti face spoofing ….Image processing ……..Feature extraction ……..Image analysis …………Image quality …………Image sequence analysis …………Image texture analysis ………… Object detection ….Statistics ……..Fisher discriminant analysis ….Algebra ……..Set theory …………Fuzzy set theory …………Rough set theory ……..Statistical analysis …………Principal component analysis …………Regression analysis …………K fold cross validation ….Algorithms ……..Machine learning algorithms iv Robotics and Artificial Intelligence Laboratory, Indian Institute of Information Technology Allahabad, India Abstract Robot cops or robot police is the new arena of robotics research. The agility in the vicinity of robotics, especially towards developing Social Robots, which can help police to identify criminals, diffuse bombs, rescuing hostages etc. has received more attention than any other. Therefore, in this thesis, we have devised four different techniques of criminal identification. Our hypothesis–“it is possible to design a robust and secure criminal identification framework which can identify the criminal based on the visual perception of the eyewitness as well as by seeing them”. In order to establish the above hypothesis several challenges of perception acquisition, representation and modeling have been addressed while an anti-face spoofing system has been created to discard imposter attacks. NAO Humanoid Robot has been utilized as a testbed to test our hypothesis. In the process of establishment of our hypothesis, the first contribution (chapter 3) processes eyewitness imprecise knowledge to trace out the criminals. An eyewitness’s visual perception about the criminal is first captured with the help of a dialogue based Humanoid Robot framework. The captured inferences are vague hence a linear transformation is applied to quantize this information. The quantized information is then modeled with the help of our proposed decision tree (query based) and rough set based approaches. Two case studies, viewed and forensic sketches have been considered to evaluate the strength of our proposed approach. A symbolic database has been created to perform a stringent analysis on 240 public faces (150 public Bollywood celebrities and Indian cricketers, 90 local faces (our dataset)) in case of query based approach, while the benchmark mugshot criminal database of 300 persons from Chinese University of Hong Kong, has been utilized to evaluate the rough set based modeling. The building block of the human perception based criminal identification is laid down on the assumption that criminals must be enrolled in the system. The approach fails to produce the wanted results when the criminal information is not registered in the system (in case of international criminal or she/he is committing crime first time). Towards the solution of this problem, in Chapter 4, we have trained humanoid robot to perform sketch v Robotics and Artificial Intelligence Laboratory, Indian Institute of Information Technology Allahabad, India drawing of the criminals, based on the given perception about criminals. In order to mimic the drawing, two primitive challenges such as calibrating humanoid camera plane with respect to its body coordinate system and finding an inverse kinematic based solution, need to be addressed. The former problem has been solved by providing the three different mechanisms (a) 4 Point, (b) Fundamental Matrix and (c) Artificial neural network based Regression Analysis while a gradient descendent based inverse kinematic solution is utilized for the NAO Right Hand. The first two contributions empower NAO to identify and synthesis the criminal face based on eyewitness visual perception about the criminal. In the third contribution of the thesis (Chapter 5), we have designed two face recognition algorithms based on the principle of facial symmetry and component based face recognition to identify criminals seeing the face images. The facial symmetry based face recognition utilizes either part of the face (left or right) to recognize the criminal. A Principal Component Analysis based experiment performed on the AT&T face database confirms that half faces could produce almost equal accuracy as the full faces, hence can be utilized for criminal identification. This reduces the time complexity as well as helps in partial information based criminal identification. Another study on 345 public faces confirms that 80% of the face discriminant features lie only within the eyes, nose and mouth region. The proposed component based face recognition localizes the face over these components and extracts the Scale Invariant Features Transform (SIFT) features from these regions. Later the classification is performed on the basis of weightage majority voting over these extracted features. The illumination effect is almost homogeneous on the face narrower regions, therefore the proposed approach can handle the variable illumination challenges as well recognize the criminal face covered with scarf or goggles. The component based face recognition can also solve the real time challenge like change in facial expression. At last, in Chapter 6, we deployed the liveness detection mechanism over our face recognition system to detect and prevent face spoofing attacks. Face spoofing is an attack against a face recognition system to bypass the authentication system and to get unauthorized access to the system. The robot is an autonomous and re-programmable device therefore, its security must be assured. Liveness is a test to measure the life of the vi Robotics and Artificial Intelligence Laboratory, Indian Institute of Information Technology Allahabad, India presented biometric in order to discard spoof attacks. Movement in facial macro features such as facial expressions and face 3D structure have been utilized to design the liveness test. The facial movement based face spoofing detection is based on the challenge and response mechanism while to evaluate the 3D structure, NAO stereo-vision has been exploited. The human perception based criminal identification allows humanoid robots to identify criminals using the rough idea about the criminal physiological as well as facial descriptions. The sketch drawing capability empowers humanoids to synthesis the criminal face using the same facial description. The facial symmetry and component based face recognition facilitates them to recognize criminals even her/his face is occluded with scarf/googles or any other object. The addition of face liveness detection on top of face recognition secures the overall system to prevent from unauthorized access. The proposed framework has been
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