The objective of this thesis is to detect and identify moving objects in a video sequence. The currently available techniques for motion estimation can be broadly categorized into two main classes: block matching methods and optical flow methods.<p>This thesis investigates the different motion estimation algorithms used for video processing applications. Among the available motion estimation methods, the Lucas Kanade Optical Flow Algorithm has been used in this thesis for detection of moving objects in a video sequence. Derivatives of image brightness with respect to x-direction, y-direction and time t are calculated to solve the Optical Flow Constraint Equation. The algorithm produces results in the form of horizontal and vertical components of optical flow velocity, u and v respectively. This optical flow velocity is measured in the form of vectors and has been used to segment the moving objects from the video sequence. The algorithm has been applied to different sets of synthetic and real video sequences.<p>This method has been modified to include parameters such as neighborhood size and Gaussian pyramid filtering which improve the motion estimation process. The concept of Gaussian pyramids has been used to simplify the complex video sequences and the optical flow algorithm has been applied to different levels of pyramids. The estimated motion derived from the difference in the optical flow vectors for moving objects and stationary background has been used to segment the moving objects in the video sequences. A combination of erosion and dilation techniques is then used to improve the quality of already segmented content.<p>The Lucas Kanade Optical Flow Algorithm along with other considered parameters produces encouraging motion estimation and segmentation results. The consistency of the algorithm has been tested by the usage of different types of motion and video sequences. Other contributions of this thesis also include a comparative analysis of the optical flow algorithm with other existing motion estimation and segmentation techniques. The comparison shows that there is need to achieve a balance between accuracy and computational speed for the implementation of any motion estimation algorithm in real time for video surveillance.

The objective of this thesis is to detect and identify moving objects in a video sequence. The currently available techniques for motion estimation can be broadly categorized into two main classes: block matching methods and optical flow methods.<p>This thesis investigates the different motion estimation algorithms used for video processing applications. Among the available motion estimation methods, the Lucas Kanade Optical Flow Algorithm has been used in this thesis for detection of moving objects in a video sequence. Derivatives of image brightness with respect to x-direction, y-direction and time t are calculated to solve the Optical Flow Constraint Equation. The algorithm produces results in the form of horizontal and vertical components of optical flow velocity, u and v respectively. This optical flow velocity is measured in the form of vectors and has been used to segment the moving objects from the video sequence. The algorithm has been applied to different sets of synthetic and real video sequences.<p>This method has been modified to include parameters such as neighborhood size and Gaussian pyramid filtering which improve the motion estimation process. The concept of Gaussian pyramids has been used to simplify the complex video sequences and the optical flow algorithm has been applied to different levels of pyramids. The estimated motion derived from the difference in the optical flow vectors for moving objects and stationary background has been used to segment the moving objects in the video sequences. A combination of erosion and dilation techniques is then used to improve the quality of already segmented content.<p>The Lucas Kanade Optical Flow Algorithm along with other considered parameters produces encouraging motion estimation and segmentation results. The consistency of the algorithm has been tested by the usage of different types of motion and video sequences. Other contributions of this thesis also include a comparative analysis of the optical flow algorithm with other existing motion estimation and segmentation techniques. The comparison shows that there is need to achieve a balance between accuracy and computational speed for the implementation of any motion estimation algorithm in real time for video surveillance.

Detta examensarbete genomfördes på ABB Power Technologies AB i Ludvika. ABB vill överbrygga gapet mellan industri och informationsteknologi för att få de båda delarna att arbeta integrerat. ABB kallar detta koncept för Industrial IT (IIT). Ett krav från koncernledningen är att alla produkter ska vara certifierade enligt nivå 0, som är det första steget i IIT: s certifieringsprocess. Målet var att utföra en kravspecifikation på ett system som ska kunna leverera certifierad produktinformation enligt IIT-standard. Målet var även att, med kravspecifikationen som underlag, ge förslag på en lösning för att ABB ska kunna skapa och bifoga denna produktinformation till sina kunder.Det akademiska syftet var att beskriva hur man kan gå till väga för att certifiera produktinformationen enligt IIT nivå 0 på en produkt i ABB: s verksamhet. Syftet var även att öka förståelsen för IIT-konceptet.Genom hela arbetet har Gatemodellen använts. Denna projektstyrningsmodell är framtagen speciellt för informationssystem-projekt inom ABB och alla projekt som utförs inom ABB ska följa den. För att uppfylla målet med en utförd kravspecifikation har relevanta delar ur Directmodellen använts. För att få information om hur verksamheten fungerar och få insikt i problematiken har intervjuer genomförts som grundar sig på litteraturstudier.Vi föreslår att ett tidigare utgivet system vid namn Aspect Object Builder (AOB) används som grund i det här projektet. AOB: n har använts i liknande projekt inom ABB och fungerat bra. Det finns ingen standardkoppling mellan AOB: n och de system där produktinformationen finns eftersom det finns så många olika typer av filservrar, PDM- och ERP-system, där informationen lagras. Därför måste ett unikt gränssnitt göras för just detta projekt, som hjälper AOB: n att samla in data. Ett förslag till ett gränssnitt presenteras i uppsatsen.

Shared objects are a key component in today's large distributed systems. Linearizability is a popular consistency condition for such shared objects which gives the illusion of sequential execution of operations. The time bound of an operation is the worst-case time complexity from the operation invocation to its response. Some time bounds have been proved for certain operations on linearizable shared objects in partially synchronous systems but there are some gaps between time upper bound and lower bound for each operation. In this work, the goal is to narrow or eliminate the gaps and find optimally fast implementations. To reach this goal, we prove larger lower bounds and show smaller upper bounds (compared to 2d for all operations in previous folklore implementations) by proposing an implementation for a shared object with an arbitrary data type in distributed systems of n processes in which every message delay is bounded within [d-u, d] and the maximum skew between processes' clocks is epsilon. Considering any operation for which there exist two instances such that individually, each instance is legal but in sequence they are not, we prove a lower bound of d + min{epsilon, u, d/3}, improving from d, and show this bound is tight when epsilon < d/3 and epsilon < u. Considering any operation for which there exist k instances such that each instance separately is legal and any sequence of them is legal, but the state of the object is different after different sequences, we prove a lower bound of (1-1/k)u, improving from u/2, and show this bound is tight when k = n. A pure mutator only modifies the object but does not return anything about the object. A pure accessor does not modify the object. For a pure mutator OP1 and a pure accessor OP2, if given a set of instances of OP1, the state of the object reflects the order in which the instances occur and an instance of OP2 can detect whether an instance of OP1 occurs, we prove the sum of the time bound for OP1 and OP2 is at least d + min{epsilon, u, d/3}, improving from d. The upper bound is d + 2*epsilon from our implementation.

The science fiction cinema is often concerned about future, and presents to its audience possible alternatives for it. Each science fiction film about the future constructs a different idea in the audience&rsquo / s mind and supports a currently existing ideology at the same time. The science fiction genre extrapolates and speculates about future which results in a new world: Aliens, androids or clones become participants of this world, intergalactic federations regulate diplomatic relationships or natural disasters endanger the whole humankind. The indispensable factor in every case is that new objects surround the future. They are extrapolated or speculated as well from the objects of today in order to fit to and satisfy the needs of the future world of the science fiction film. The ideas about the future presented in the film are supported by the material existence of these future objects. This study demonstrates the ideas and ideologies in respect to future in the science fiction cinema and investigates how the future objects contribute to constructing them.

For some new multimedia applications using Mpeg-4 or Mpeg-7 video coding standards, it is important to find the main objects in a video frame. In this thesis, we propose a neuro-fuzzy modeling approach to the detection of human face and body. Firstly, a fuzzy clustering technique is performed to segment a video frame into clusters to generating several fuzzy rules. Secondly, chrominance and motion features are used to roughly classify the clusters into foreground and background, respectively. Finally, the fuzzy rules are refined by a fuzzy neural network, and the ambiguous regions between foreground and background are further distinguished by the fuzzy neural network. Our method improves the correctness of human face and body detection by getting training data more precisely. Besides, we can extract the VOs correctly even the VOs have no obvious motion in the video sequence.

"A thesis submitted to the Graduate Faculty of Georgia Southern University in partial fulfillment of the requirements for the degree Master of Fine Art." Title from PDF of title page (Georgia Southern University, viewed on February 10, 2010). Marc Moulton, committee chair; Bruce Little, Julie McGuire, Gary Dartt, committee members. Electronic version approved: December 2009. Includes bibliographical references (p. 119-121).

Zugl.: Mannheim, Univ., Diss., 2007

Thesis (M.F.A.)--Kent State University, 2009. / Title from PDF t.p. (viewed Jan. 22, 2010). Advisor: Darice Polo. Keywords: Installation; assemblage; mixed-media; drawing; playful arrangements; doodling; envrionmental art; intuitive process; mixed-media drawings; environmental concerns; ecological concerns; fragile environment; site-specific; craft-based methods; post-consumer. Includes bibliographical references (p. 28).

The following graduate report is an overview of my artistic endeavors spanning the past three years at the University of Texas at Austin. While at UT, I have concentrated on making paintings that focus on the relationship between abstraction, representation, and entropy. Using banal, often overlooked cultural objects as subject matter, I paint ambiguous scenes that teeter between disintegration and formation. Representations of banal detritus within an ambiguous natural space become a metaphor for memory, culture, and life and death alluding to unseen forces and, ultimately, a lack of control. Using a combination of random and deliberate decisions, I aim to create a commentary about the unpredictable yet conformist aspects of the world in which we participate. / text