Hasil untuk "Motion pictures"

Ana Cordon-Avila, Mostafa Selim, Momen Abayazid

Respiratory motion limits the accuracy and precision of abdominal percutaneous procedures. In this paper, respiratory motion is compensated robotically using motion estimation models. Additionally, a teleoperated insertion is performed using proximity-based haptic feedback to guide physicians during insertion, enabling a radiation-free remote insertion for the end-user. The study has been validated using a robotic liver phantom, and five insertions were performed. The resulting motion estimation errors were below 3 mm for all directions of motion, and the overall resulting 3D insertion errors were 2.60, 7.75, and 2.86 mm for the superior-inferior, lateral, and anterior-posterior directions of motion, respectively. The proposed approach is expected to minimize the chances of inaccurate treatment or diagnosis due to respiratory-induced motion and reduce radiation exposure.

Charles Alexandre Bédard

The standard claim that the Schrödinger and Heisenberg pictures of quantum mechanics are equivalent rests on the fact that they yield identical empirical predictions. This equivalence therefore assumes the instrumentalist worldview in which theories serve only as tools for prediction. Under scientific realism, by contrast, theories aim to describe reality. Whereas the Schrödinger picture posits a time-evolving wave function, the Heisenberg picture posits so-called descriptors, time-evolving generators of the algebra of observables. These two structures are non-isomorphic: descriptors surject onto but do not reduce to the Schrödinger state. Hence, under realism, the pictures are inequivalent. I argue that this inequivalence marks an opening toward a richer, separable ontology for quantum theory. On explanatory grounds, descriptors provide genuinely local accounts of superdense coding, teleportation, branching, and Bell inequality violations -- phenomena that the Schrödinger framework does not explain fully locally.

Tatjana Zähringer, Raimund Girwidz, Andreas Müller

Pictures in physics education go beyond instructional functions and serve affective roles, such as attracting attention, creating fascination, and fostering engagement with the depicted content. Recognizing the importance of these affective functions highlights the need to understand and utilize aesthetic pictures in a research-based educational environment. Prior research suggests that aesthetic and affective attractiveness in pictures enhances enjoyment and engagement with the physics content. This paper offers three main contributions: Firstly, it conceptualizes and presents research-based criteria for selecting pictures perceived as aesthetically pleasing, drawing on insights from psychology and physics education research. Following these criteria, aesthetic pictures related to a given curricular content can be selected. Secondly, the paper applies these criteria to selecting pictures showing geometrical optics. It then delves into an evaluation of students' aesthetic and affective perception of the selected pictures. A validated instrument measured these responses, showing strong reliability (aesthetic perception: $α_C$ = 0.87 [0.85, 0.89]; affective perception: $α_C$ = 0.82 [0.80, 0.85]). Thirdly, it combines decorative and instructional functions in tasks and compares students' perceptions of aesthetic pictures (AP) and classroom experiment pictures (CEP) in junior high school ($N$ = 118), using a crossover design. Results indicated significantly better aesthetic and affective evaluations for APs, with large effect sizes (AP vs. CEP, aesthetic and affective perception: $d$ = 1.05 - 1.56 and 0.85 - 1.48, respectively). We conclude that the here developed and investigated criteria are useful for selecting aesthetic and affective pictures. This provides a basis for further leveraging their educational potential to create fascination and engagement in science education.

Vasileios Vasilopoulos, Sebastian Castro, William Vega-Brown et al.

We describe a task and motion planning architecture for highly dynamic systems that combines a domain-independent sampling-based deliberative planning algorithm with a global reactive planner. We leverage the recent development of a reactive, vector field planner that provides guarantees of reachability to large regions of the environment even in the face of unknown or unforeseen obstacles. The reachability guarantees can be formalized using contracts that allow a deliberative planner to reason purely in terms of those contracts and synthesize a plan by choosing a sequence of reactive behaviors and their target configurations, without evaluating specific motion plans between targets. This reduces both the search depth at which plans will be found, and the number of samples required to ensure a plan exists, while crucially preserving correctness guarantees. The result is reduced computational cost of synthesizing plans, and increased robustness of generated plans to actuator noise, model misspecification, or unknown obstacles. Simulation studies show that our hierarchical planning and execution architecture can solve complex navigation and rearrangement tasks, even when faced with narrow passageways or incomplete world information.

Haoyue Tian, Pan Gao, Ran Wei et al.

Motion estimation and motion compensation are indispensable parts of inter prediction in video coding. Since the motion vector of objects is mostly in fractional pixel units, original reference pictures may not accurately provide a suitable reference for motion compensation. In this paper, we propose a deep reference picture generator which can create a picture that is more relevant to the current encoding frame, thereby further reducing temporal redundancy and improving video compression efficiency. Inspired by the recent progress of Convolutional Neural Network(CNN), this paper proposes to use a dilated CNN to build the generator. Moreover, we insert the generated deep picture into Versatile Video Coding(VVC) as a reference picture and perform a comprehensive set of experiments to evaluate the effectiveness of our network on the latest VVC Test Model VTM. The experimental results demonstrate that our proposed method achieves on average 9.7% bit saving compared with VVC under low-delay P configuration.

Anne Metcalf

Anne Gilbert

This article addresses streaming television platforms’ reliance on algorithms, serial narratives, and user interfaces and the effect of these strategies on the television viewing audience. The datafication of television means that opaque, proprietary computational processes play a significant role in the television that gets made, in steering viewing to particular series, and in reshaping the identity of the viewing public. User interfaces, data tracking, seriality, and algorithms have thus far proven inadequate for navigating the vast databases offered by streaming platforms. In practice, these systems off-load work to viewers and actively create obstacles to the formation of a collective viewing experience. Algorithmic audiences are trained to be sequential, isolated viewers, whose work of watching occurs in labor-intensive ways.

Damian Moctezuma Enriquez, Eduardo Rodarte Leyva

An Schematical Design for an Autonomous Picture taker used for obtaining Point clouds from pictures taken inside a House. In this case we are proposing the use of an equation programmed inside an embedded system that will be tracking the points inside a room and then, open the space between two cameras of same type in order to take pictures that later will be used to create the cloud points for the mathematical model that the latter user will apply to that pictures.

Debajit Sarma, V. Kavyasree, M. K. Bhuyan

The use of hand gestures can be a useful tool for many applications in the human-computer interaction community. In a broad range of areas hand gesture techniques can be applied specifically in sign language recognition, robotic surgery, etc. In the process of hand gesture recognition, proper detection, and tracking of the moving hand become challenging due to the varied shape and size of the hand. Here the objective is to track the movement of the hand irrespective of the shape, size, and color of the hand. And, for this, a motion template guided by optical flow (OFMT) is proposed. OFMT is a compact representation of the motion information of a gesture encoded into a single image. In the experimentation, different datasets using bare hand with an open palm, and folded palm wearing green-glove are used, and in both cases, we could generate the OFMT images with equal precision. Recently, deep network-based techniques have shown impressive improvements as compared to conventional hand-crafted feature-based techniques. Moreover, in the literature, it is seen that the use of different streams with informative input data helps to increase the performance in the recognition accuracy. This work basically proposes a two-stream fusion model for hand gesture recognition and a compact yet efficient motion template based on optical flow. Specifically, the two-stream network consists of two layers: a 3D convolutional neural network (C3D) that takes gesture videos as input and a 2D-CNN that takes OFMT images as input. C3D has shown its efficiency in capturing spatio-temporal information of a video. Whereas OFMT helps to eliminate irrelevant gestures providing additional motion information. Though each stream can work independently, they are combined with a fusion scheme to boost the recognition results. We have shown the efficiency of the proposed two-stream network on two databases.

Mete Sertkan, Julia Neidhardt, Hannes Werthner

Eliciting the preferences and needs of tourists is challenging, since people often have difficulties to explicitly express them, especially in the initial phase of travel planning. Recommender systems employed at the early stage of planning can therefore be very beneficial to the general satisfaction of a user. Previous studies have explored pictures as a tool of communication and as a way to implicitly deduce a traveller's preferences and needs. In this paper, we conduct a user study to verify previous claims and conceptual work on the feasibility of modelling travel interests from a selection of a user's pictures. We utilize fine-tuned convolutional neural networks to compute a vector representation of a picture, where each dimension corresponds to a travel behavioural pattern from the traditional Seven-Factor model. In our study, we followed strict privacy principles and did not save uploaded pictures after computing their vector representation. We aggregate the representations of the pictures of a user into a single user representation, i.e., touristic profile, using different strategies. In our user study with 81 participants, we let users adjust the predicted touristic profile and confirm the usefulness of our approach. Our results show that given a collection of pictures the touristic profile of a user can be determined.

William Brown

Luciana de Castro Nunes Novaes

Esse texto resulta de um filme que não foi editado. As gravações foram realizadas objetivando as jangadas de pau fundeadas na Praia do Flamengo, Salvador, Bahia, Brasil. A expressão “making the making” é utilizada nesse artigo para refletir sobre a potência da fotografia em contextos de produção audiovisual, a confecção do roteiro a partir da autoria compartilhada entre pesquisadoras e personagem central e a construção política de um filme etnográfico.

Rhys Newbury, Akansel Cosgun, Mehmet Koseoglu et al.

We present a robotic system capable of navigating autonomously by following a line and taking good quality pictures of people. When a group of people are detected, the robot rotates towards them and then back to line while continuously taking pictures from different angles. Each picture is processed in the cloud where its quality is estimated in a two-stage algorithm. First, features such as the face orientation and likelihood of facial emotions are input to a fully connected neural network to assign a quality score to each face. Second, a representation is extracted by abstracting faces from the image and it is input to a to Convolutional Neural Network (CNN) to classify the quality of the overall picture. We collected a dataset in which a picture was labeled as good quality if subjects are well-positioned in the image and oriented towards the camera with a pleasant expression. Our approach detected the quality of pictures with 78.4% accuracy in this dataset and received a better mean user rating (3.71/5) than a heuristic method that uses photographic composition procedures in a study where 97 human judges rated each picture. A statistical analysis against the state-of-the-art verified the quality of the resulting pictures.

C. A. Cremonini, P. A. Grassi

We study super-Chern-Simons theory on a generic supermanifold. After a self-contained review of integration on supermanifolds, the complexes of forms (superforms, pseudo-forms and integral forms) and the extended Cartan calculus are discussed. We then introduce Picture Changing Operators. We provide several examples of computation of PCO's acting on different type of forms. We illustrate also the action of the $η$ operator, crucial ingredient to define the interactions of super Chern-Simons theory. Then, we discuss the action for super Chern-Simons theory on any supermanifold, first in the factorized form (3-form $\times$ PCO) and then, we consider the most general expression. The latter is written in term of psuedo-forms containing an infinite number of components. We show that the free equations of motion reduce to the usual Chern-Simons equations yielding the proof of the equivalence between the formulations at different pictures of the same theory. Finally, we discuss the interaction terms. They require a suitable definition in order to take into account the picture number. That implies the construction of a 2-product which is not associative that inherits an $A_\infty$ algebra structure. That shares several similarities with a recent construction of a super string field theory action by Erler, Konopka and Sachs.

B. J. Hiley, G. Dennis

We examine Dirac's early algebraic approach which introduces the {\em standard} ket and show that it emerges more clearly from a unitary transformation of the operators based on the action. This establishes a new picture that is unitarily equivalent to both the Schrödinger and Heisenberg pictures. We will call this the Dirac-Bohm picture for the reasons we discuss in the paper. This picture forms the basis of the Feynman path theory and allows us to show that the so-called `Bohm trajectories' are averages of an ensemble of Feynman paths.

Arthur Jaffe, Zhengwei Liu

We give an overview of our philosophy of pictures in mathematics. We emphasize a bi-directional process between picture language and mathematical concepts: abstraction and simulation. This motivates a program to understand different subjects, using virtual and real mathematical concepts simulated by pictures.

David H. Fleming

Florian Willomitzer, Gerd Häusler

We introduce a method and a 3D-camera for single-shot 3D shape measurement, with unprecedented features: The 3D-camera does not rely on pattern codification and acquires object surfaces at the theoretical limit of the information efficiency: Up to 30% of the available camera pixels display independent (not interpolated) 3D points. The 3D-camera is based on triangulation with two properly positioned cameras and a projected multi-line pattern, in combination with algorithms that solve the ambiguity problem. The projected static line pattern enables 3D-acquisition of fast processes and the take of 3D-motion-pictures. The depth resolution is at its physical limit, defined by electronic noise and speckle noise. The requisite low cost technology is simple.

Anna Seigal

The cover of the SIAM Journal on Applied Algebra and Geometry shows seven pictures. We describe these pictures and discuss the topics they represent. About the Author: Anna Seigal is a graduate student at UC Berkeley working in applied algebra. Her interests lie in tensors and applications to biological systems. She has a particular penchant for writing about mathematics in terms of pictures and also blogs on this subject at https://picturethismaths.wordpress.com/.

Javier Olmedo

We study the relation between two evolution pictures that are currently considered for totally constrained theories. Both descriptions are based on Rovelli's evolving constants approach, where one identifies a (possibly local) degree of freedom of the system as an internal time. This method is well understood classically in several situations. The purpose of this paper is to further analyze this approach at the quantum level. Concretely, we will compare the (Schrödinger-like) picture where the physical states evolve in time with the (Heisenberg-like) picture in which one defines parametrized observables (or evolving constants of the motion). We will show that in the particular situations considered in this manuscript (the parametrized relativistic particle and a spatially flat homogeneous and isotropic spacetime coupled to a massless scalar field) both descriptions are equivalent. We will finally comment on possible issues and on the genericness of the equivalence between both pictures.