Development Of Intersecting And Non-Intersecting Volumetric Feature Recognition Techniques In A Platform-Dependent System

The feature recognition process has been considered as the input for Computer-aided Process Planning through two different standpoints in implementation, one is nonfeature-based and the other is feature-based .The first one is done via accessing to the information of part (e.g. edges, faces,…) from within standard files with neutral data format (DXF/IGES/STEP) and then is conducted by connecting to the objects library of design-by-feature solid modeler. The second method has currently received extensive attention due to accessing to significant information effortlessly and handling intersecting and non-intersecting features. In this thesis, the feature-based design is exploited for converting design feature into manufacturing feature aimed to recognize the various intersecting and non-intersecting volumetric features. The rule-based, graph-based, and mathematical algorithms are used to recognize the intersecting and non-intersecting features with their volume. The ability and robustness of proposed methods in identifying the protrusion/subtractive features which are made on slanting/planar surfaces, is represented by implementing software on a commercial Computer-aided design package, Autodesk Inventor

"'Who are you?' - Learning person specific classifiers from video"

We investigate the problem of automatically labelling faces of characters in TV or movie material with their names, using only weak supervision from automaticallyaligned subtitle and script text. Our previous work (Everingham et al. [8]) demonstrated promising results on the task, but the coverage of the method (proportion of video labelled) and generalization was limited by a restriction to frontal faces and nearest neighbour classification. In this paper we build on that method, extending the coverage greatly by the detection and recognition of characters in profile views. In addition, we make the following contributions: (i) seamless tracking, integration and recognition of profile and frontal detections, and (ii) a character specific multiple kernel classifier which is able to learn the features best able to discriminate between the characters. We report results on seven episodes of the TV series “Buffy the Vampire Slayer”, demonstrating significantly increased coverage and performance with respect to previous methods on this material

Invariant Spectral Hashing of Image Saliency Graph

Image hashing is the process of associating a short vector of bits to an image. The resulting summaries are useful in many applications including image indexing, image authentication and pattern recognition. These hashes need to be invariant under transformations of the image that result in similar visual content, but should drastically differ for conceptually distinct contents. This paper proposes an image hashing method that is invariant under rotation, scaling and translation of the image. The gist of our approach relies on the geometric characterization of salient point distribution in the image. This is achieved by the definition of a saliency graph connecting these points jointly with an image intensity function on the graph nodes. An invariant hash is then obtained by considering the spectrum of this function in the eigenvector basis of the graph Laplacian, that is, its graph Fourier transform. Interestingly, this spectrum is invariant under any relabeling of the graph nodes. The graph reveals geometric information of the image, making the hash robust to image transformation, yet distinct for different visual content. The efficiency of the proposed method is assessed on a set of MRI 2-D slices and on a database of faces

Trees of nuclei and bounds on the number of triangulations of the 3-ball

Based on the work of Durhuus-J{\'o}nsson and Benedetti-Ziegler, we revisit the question of the number of triangulations of the 3-ball. We introduce a notion of nucleus (a triangulation of the 3-ball without internal nodes, and with each internal face having at most 1 external edge). We show that every triangulation can be built from trees of nuclei. This leads to a new reformulation of Gromov's question: We show that if the number of rooted nuclei with $t$ tetrahedra has a bound of the form $C^t$, then the number of rooted triangulations with $t$ tetrahedra is bounded by $C_*^t$

Steinitz Theorems for Orthogonal Polyhedra

We define a simple orthogonal polyhedron to be a three-dimensional polyhedron with the topology of a sphere in which three mutually-perpendicular edges meet at each vertex. By analogy to Steinitz's theorem characterizing the graphs of convex polyhedra, we find graph-theoretic characterizations of three classes of simple orthogonal polyhedra: corner polyhedra, which can be drawn by isometric projection in the plane with only one hidden vertex, xyz polyhedra, in which each axis-parallel line through a vertex contains exactly one other vertex, and arbitrary simple orthogonal polyhedra. In particular, the graphs of xyz polyhedra are exactly the bipartite cubic polyhedral graphs, and every bipartite cubic polyhedral graph with a 4-connected dual graph is the graph of a corner polyhedron. Based on our characterizations we find efficient algorithms for constructing orthogonal polyhedra from their graphs.Comment: 48 pages, 31 figure