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Tomasi–Kanade Factorization
The Tomasi–Kanade factorization is the seminal work by Carlo Tomasi and Takeo Kanade in the early 1990s. It charted out an elegant and simple solution based on a SVD-based factorization scheme for analysing image measurements of a rigid object captured from different views using a weak perspective camera model. The crucial observation made by authors was that if all the measurements (i.e., image co-ordinates of all the points in all the views) are collected in a single matrix, the point trajectories will reside in a certain subspace. The dimension of the subspace in which the image data resides is a direct consequence of two factors: # The type of camera that projects the scene (for example, affine or perspective) # The nature of inspected object (for instance, rigid or non-rigid). The low-dimensionality of the subspace is mirrored (captured) trivially as reduced rank of the measurement matrix. This reduced rank of measurement matrix can be motivated from the fact that, the po ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Takeo Kanade
is a Japanese computer scientist and one of the world's foremost researchers in computer vision. He is Uncas A. Whitaker, U.A. and Helen Whitaker Professor at Carnegie Mellon University. He has approximately 300 peer-reviewed academic publications and holds around 20 patents. Honors and achievements * In 1997, he was elected to the US National Academy of Engineering for contributions to computer vision and robotics. * In 1997, he was elected to the American Academy of Arts and Sciences * In 1999 he was inducted as a Fellow of the Association for Computing Machinery. * In 2008 Kanade received the The Franklin Institute Awards, Bower Award and Prize for Achievement in Science from The Franklin Institute in Philadelphia, Pennsylvania. * A special event called TK60: Celebrating Takeo Kanade's vision was held to commemorate his 60th birthday. This event was attended by prominent computer vision researchers. * Elected member of American Association of Artificial Intelligence, Robotics ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Singular-value Decomposition
In linear algebra, the singular value decomposition (SVD) is a factorization of a real or complex matrix. It generalizes the eigendecomposition of a square normal matrix with an orthonormal eigenbasis to any \ m \times n\ matrix. It is related to the polar decomposition. Specifically, the singular value decomposition of an \ m \times n\ complex matrix is a factorization of the form \ \mathbf = \mathbf\ , where is an \ m \times m\ complex unitary matrix, \ \mathbf\ is an \ m \times n\ rectangular diagonal matrix with non-negative real numbers on the diagonal, is an n \times n complex unitary matrix, and \ \mathbf\ is the conjugate transpose of . Such decomposition always exists for any complex matrix. If is real, then and can be guaranteed to be real orthogonal matrices; in such contexts, the SVD is often denoted \ \mathbf^\mathsf\ . The diagonal entries \ \sigma_i = \Sigma_\ of \ \mathbf\ are uniquely determined by and are known as the singular values of . The ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
3D Projection
A 3D projection (or graphical projection) is a design technique used to display a three-dimensional (3D) object on a two-dimensional (2D) surface. These projections rely on visual perspective and aspect analysis to project a complex object for viewing capability on a simpler plane. 3D projections use the primary qualities of an object's basic shape to create a map of points, that are then connected to one another to create a visual element. The result is a graphic that contains conceptual properties to interpret that the figure or image as not actually flat (2D), but rather, as a solid object (3D) being viewed on a 2D display. 3D objects are largely displayed on two-dimensional mediums (i.e. paper and computer monitors). As such, graphical projections are a commonly used design element; notably, in engineering drawing, drafting, and computer graphics. Projections can be calculated through employment of mathematical analysis and formulae, or by using various geometric and o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Frobenius Norm
In mathematics, a matrix norm is a vector norm in a vector space whose elements (vectors) are matrices (of given dimensions). Preliminaries Given a field K of either real or complex numbers, let K^ be the -vector space of matrices with m rows and n columns and entries in the field K. A matrix norm is a norm on K^. This article will always write such norms with double vertical bars (like so: \, A\, ). Thus, the matrix norm is a function \, \cdot\, : K^ \to \R that must satisfy the following properties: For all scalars \alpha \in K and matrices A, B \in K^, *\, A\, \ge 0 (''positive-valued'') *\, A\, = 0 \iff A=0_ (''definite'') *\left\, \alpha A\right\, =\left, \alpha\ \left\, A\right\, (''absolutely homogeneous'') *\, A+B\, \le \, A\, +\, B\, (''sub-additive'' or satisfying the ''triangle inequality'') The only feature distinguishing matrices from rearranged vectors is multiplication. Matrix norms are particularly useful if they are also sub-multiplicative: *\left\, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Structure From Motion
Structure from motion (SfM) is a photogrammetric range imaging technique for estimating three-dimensional structures from two-dimensional image sequences that may be coupled with local motion signals. It is studied in the fields of computer vision and visual perception. In biological vision, SfM refers to the phenomenon by which humans (and other living creatures) can recover 3D structure from the projected 2D (retinal) motion field of a moving object or scene. Principle Humans perceive a great deal of information about the three-dimensional structure in their environment by moving around it. When the observer moves, objects around them move different amounts depending on their distance from the observer. This is known as motion parallax, and from this depth information can be used to generate an accurate 3D representation of the world around them. Finding structure from motion presents a similar problem to finding structure from stereo vision. In both instances, the correspo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Motion In Computer Vision
In physics, motion is the phenomenon in which an object changes its position with respect to time. Motion is mathematically described in terms of displacement, distance, velocity, acceleration, speed and frame of reference to an observer and measuring the change in position of the body relative to that frame with change in time. The branch of physics describing the motion of objects without reference to its cause is called kinematics, while the branch studying forces and their effect on motion is called dynamics. If an object is not changing relative to a given frame of reference, the object is said to be ''at rest'', ''motionless'', ''immobile'', '' stationary'', or to have a constant or time-invariant position with reference to its surroundings. Modern physics holds that, as there is no absolute frame of reference, Newton's concept of '' absolute motion'' cannot be determined. As such, everything in the universe can be considered to be in motion. Motion applies to various ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
