Revisión de literatura de jerarquía volúmenes acotantes enfocados en detección de colisiones

(Eng) A bounding volume is a common method to simplify object representation by using the composition of geometrical shapes that enclose the object; it encapsulates complex objects by means of simple volumes and it is widely useful in collision detection applications and ray tracing for rendering algorithms. They are popular in computer graphics and computational geometry. Most popular bounding volumes are spheres, Oriented-Bounding Boxe s (OBB’ s), Axis-Align ed Bound ing Boxes (AABB’ s); moreover , the literature review includes ellipsoids, cylinders, sphere packing, sphere shells , k-DOP’ s, convex hulls, cloud of points, and minimal bounding boxe s, among others. A Bounding Volume Hierarchy is ussualy a tree in which the complete object is represented thigter fitting every level of the hierarchy. Additionally, each bounding volume has a cost associated to construction, update, and interference te ts. For instance, spheres are invariant to rotation and translations, then they do not require being updated ; their constructions and interference tests are more straightforward then OBB’ s; however, their tightness is lower than other bounding volumes. Finally , three comparisons between two polyhedra; seven different algorithms were used, of which five are public libraries for collision detection.(Spa) Un volumen acotante es un método común para simplificar la representación de los objetos por medio de composición de formas geométricas que encierran el objeto; estos encapsulan objetos complejos por medio de volúmenes simples y son ampliamente usados en aplicaciones de detección de colisiones y trazador de rayos para algoritmos de renderización. Los volúmenes acotantes son populares en computación gráfica y en geometría computacional; los más populares son las esferas, las cajas acotantes orientadas (OBB’s) y las cajas acotantes alineadas a los ejes (AABB’s); no obstante, la literatura incluye elipses, cilindros empaquetamiento de esferas, conchas de esferas, k-DOP’s, convex hulls, nubes de puntos y cajas acotantes mínimas, entre otras. Una jerarquía de volúmenes acotantes es usualmente un árbol, en el cual la representación de los objetos es más ajustada en cada uno de los niveles de la jerarquía. Adicionalmente, cada volumen acotante tiene asociado costos de construcción, actualización, pruebas de interferencia. Por ejemplo, las esferas so invariantes a rotación y translación, por lo tanto no requieren ser actualizadas en comparación con los AABB no son invariantes a la rotación. Por otro lado la construcción y las pruebas de solapamiento de las esferas son más simples que los OBB’s; sin embargo, el ajuste de las esferas es menor que otros volúmenes acotantes. Finalmente, se comparan dos poliedros con siete algoritmos diferentes de los cuales cinco son librerías públicas para detección de colisiones

Interseção sobre união probabilística para treinamento e avaliação de detectores de objetos orientados

Using localization loss terms based on the Intersection-over-Union (IoU) is a recent and promising trend for object detection. However, exploring such loss functions for oriented bounding boxes is a complex task since the IoU is not differentiable. In this work, we propose to represent object regions through probability density functions and define a similarity metric between two objects based on the Hellinger Distance that can be viewed as a Probabilistic IoU (ProbIoU). When Gaussian distributions are used (called Gaussian Bounding Boxes, or GBBs), the ProbIoU presents a differentiable closed-form expression that can be used as a localization loss for object detection. We present a simple mapping scheme from traditional bounding boxes to GBBs, allowing the proposed ProbIoU-based loss terms to be seamlessly integrated into any object detector. Finally, we show that GBBs can represent generic segmentation masks, and they induce a natural binary representation as elliptical regions (EGBBs) that adhere better to the segmentation masks than bounding boxes. Our experimental results show that the proposed localization loss term produces competitive results for object detection using bounding boxes and that EGBBs seem a better alternative for instance segmentation than bounding boxes.O uso de termos de perda de localização baseados no Intersection-over-Union (IoU) é uma tendência recente e promissora para detecção de objetos. No entanto, explorar tais funções de perda para caixas delimitadoras orientadas é uma tarefa desafiadora, pois a IoU não é diferenciável. Neste trabalho, propomos representar regiões de objetos através de funções de densidade de probabilidade e definir uma métrica de similaridade entre dois objetos baseada na Distância de Hellinger que pode ser vista como uma IoU Probabilística (ProbIoU). Quando são usadas distribuições gaussianas (chamadas Gaussian Bounding Boxes, ou GBBs), o ProbIoU apresenta uma expressão de forma fechada diferenciável que pode ser usada como perda de localização para detecção de objetos. Apresentamos um esquema de mapeamento simples de caixas delimitadoras tradicionais para GBBs, permitindo que os termos de perda baseados em ProbIoU propostos sejam perfeitamente integrados a qualquer detector de objetos. Finalmente, mostramos que GBBs podem representar máscaras de segmentação genéricas e induzem uma representação binária natural como regiões elípticas (EGBBs) que aderem melhor às máscaras de segmentação do que caixas delimitadoras. Nossos resultados experimentais mostram que o termo de perda de localização proposto produz resultados competitivos para detecção de objetos usando caixas delimitadoras, e que EGBBs parecem uma alternativa melhor para segmentação de instâncias do que caixas delimitadoras

Application of heavy-quark effective theory to lattice QCD: I. Power Corrections

Heavy-quark effective theory (HQET) is applied to lattice QCD with Wilson fermions at fixed lattice spacing a. This description is possible because heavy-quark symmetries are respected. It is desirable because the ultraviolet cutoff $1/a$ in current numerical work and the heavy-quark mass $m_Q$ are comparable. Effects of both short distances, a and $1/m_Q$, are captured fully into coefficient functions, which multiply the operators of the usual HQET. Standard tools of HQET are used to develop heavy-quark expansions of lattice observables and, thus, to propagate heavy-quark discretization errors. Three explicit examples are given: namely, the mass, decay constant, and semileptonic form factors of heavy-light mesons.Comment: 41 pp., no figs; Phys Rev D version, improving argument that an HQET holds for all m_Q

Collision detection in 3D space

Práce se zabývá detekcí kolizí v 3D simulačním prostoru. V první části jsou popsány nejpoužívanější algoritmy pro detekci, stejně jako některé knihovny hotových řešení. Druhá část práce obsahuje popis testovacího softwaru vytvořeného na základě knihovny OpenGL, včetně popisu důležitých částí. V poslední části práce jsou také prezentovány výsledky testování a porovnání vybraných algoritmů na vytvořených testovacích úlohách.The thesis deals with collision detection in 3D simulation space. In the first part, the most used algorithms for detection are presented as well as some complete solution libraries. The second part contains the description of the testing software, which is based on OpenGL library, including the description of important segments. The final section presents some testing problems on which the chosen algorithms were tested, results and method comparison.

Towards a High Quality Real-Time Graphics Pipeline

Modern graphics hardware pipelines create photorealistic images with high geometric complexity in real time. The quality is constantly improving and advanced techniques from feature film visual effects, such as high dynamic range images and support for higher-order surface primitives, have recently been adopted. Visual effect techniques have large computational costs and significant memory bandwidth usage. In this thesis, we identify three problem areas and propose new algorithms that increase the performance of a set of computer graphics techniques. Our main focus is on efficient algorithms for the real-time graphics pipeline, but parts of our research are equally applicable to offline rendering. Our first focus is texture compression, which is a technique to reduce the memory bandwidth usage. The core idea is to store images in small compressed blocks which are sent over the memory bus and are decompressed on-the-fly when accessed. We present compression algorithms for two types of texture formats. High dynamic range images capture environment lighting with luminance differences over a wide intensity range. Normal maps store perturbation vectors for local surface normals, and give the illusion of high geometric surface detail. Our compression formats are tailored to these texture types and have compression ratios of 6:1, high visual fidelity, and low-cost decompression logic. Our second focus is tessellation culling. Culling is a commonly used technique in computer graphics for removing work that does not contribute to the final image, such as completely hidden geometry. By discarding rendering primitives from further processing, substantial arithmetic computations and memory bandwidth can be saved. Modern graphics processing units include flexible tessellation stages, where rendering primitives are subdivided for increased geometric detail. Images with highly detailed models can be synthesized, but the incurred cost is significant. We have devised a simple remapping technique that allowsfor better tessellation distribution in screen space. Furthermore, we present programmable tessellation culling, where bounding volumes for displaced geometry are computed and used to conservatively test if a primitive can be discarded before tessellation. We introduce a general tessellation culling framework, and an optimized algorithm for rendering of displaced Bézier patches, which is expected to be a common use case for graphics hardware tessellation. Our third and final focus is forward-looking, and relates to efficient algorithms for stochastic rasterization, a rendering technique where camera effects such as depth of field and motion blur can be faithfully simulated. We extend a graphics pipeline with stochastic rasterization in spatio-temporal space and show that stochastic motion blur can be rendered with rather modest pipeline modifications. Furthermore, backface culling algorithms for motion blur and depth of field rendering are presented, which are directly applicable to stochastic rasterization. Hopefully, our work in this field brings us closer to high quality real-time stochastic rendering

Active Vision for Scene Understanding

Visual perception is one of the most important sources of information for both humans and robots. A particular challenge is the acquisition and interpretation of complex unstructured scenes. This work contributes to active vision for humanoid robots. A semantic model of the scene is created, which is extended by successively changing the robot\u27s view in order to explore interaction possibilities of the scene

Older Baby Boomers seeking collegiate degrees: Developmental influences on educational and vocational aspirations

Several national trends are converging to impact adult education today. First, the increasing presence of adults in higher education is accentuated by the expansive Baby Boom generation who are demanding greater access to the higher education system in the United States. Second, regarding workforce and economic development in the 21st century, employers in many industries are experiencing a workforce shortage in both numbers and skill levels of employees (Schultz, 2001; Stein, 2000). Even though four out of five Baby Boomers desire to continue working beyond typical retirement age, many will require upgraded skills and credentials (Freedman, 2005b). A third significant trend impacting adult education is longer life expectancy--age 77 today compared to age 47 in 1900 (Zeiss, 2006). The resulting longer life after traditional retirement age has encouraged older adults to participate in activities that involve new experiences, contributions to society, and learning. We need a deeper understanding of how adult learners--particularly those who are at or near traditional retirement age--access institutions of higher education, experience successful learning in their higher education endeavors, and plan to utilize their college education in their remaining work-lives. The purpose of this phenomenological study is to explore the experiences of degree-seeking, adult learners--specifically, nine Older Baby Boomers (OBB) born between 1946 and 1958 and enrolled in a Midwestern university--to understand how psychosocial, cognitive, and spiritual dimensions of adult development influenced both their transformative learning experiences in higher education and their future vocational aspirations. Persistent patterns of findings emerged from the data, including, but not limited to, the following: adult learner characteristics and reasons for enrollment; higher education support needs; adult transformative learning; self-identified cognitive, psychosocial, and spiritual development; vocational concerns of meaning, purpose, and service; and spiritual influences on future aspirations. These findings reveal the essence of the phenomenon of older adults pursuing higher education degrees, as perceived by these OBB participants, to be a self-identified transformative process resulting in improved learner self-efficacy, and acquired within a supportive, adult-friendly higher education environment which enabled students to successfully transition not only toward degree completion and ensuing career enhancements, but toward meaningful vocational aspirations grounded in personal spiritual beliefs. This complex statement engenders numerous possibilities to explore in the alternate dissertation format which includes three chapters of findings submitted to scholarly journals for publication. Each journal article centers on an overarching research question relevant to the original proposed study and is framed within one portion of Nancy Schlossberg\u27s transition model--moving in, moving through, and moving out from college. The first article addresses the student experience of OBB transitioning back into college. The second article examines the learning experience (and consequential transformation) of OBB students as they move through college. The third article explores OBB students\u27 future aspirations beyond college, including the impact of spirituality on their vocational and retirement plans. Higher education must respond to adult learners\u27 support needs, learning preferences, and vocational tendencies toward service-related encore careers. By helping older adult students prepare for careers about people, purpose, and community, colleges will capture a new population of students to serve, will help millions of people find greater significance and purpose in life, and will help sustain America\u27s strong economy (Zeiss, 2006, p. 40)