A transputer Based Laser Scanning System

This paper presents a transputer-based laser scanner. This is to be integrated into an existing transputer-based mariufacturing environment to allow rapid construction of' 3-0 models. The approach allows Z-gradient informaticm to be obtained from a 2-D image by illuminating areas of interest with a form of structured light. An active scanning system is described. Simple algorithms are applied to the raw image data to extract concise information. This foveal analysis greatly reduces the data to be processed, allowing a simple and fast method for analysis. The system primarily consists of a video camera wlhich obliquely views a scene being scanned by a laser. The principle, the procedure, and methods of scanning are described. An overview of the principles of foveal analysis, the prototype experimental system and initial results are presented

The RobotCub Approach to the Development of Cognition

This paper elaborates on the workplan of an initiative in embodied cognition: RobotCub. Our goal here is to provide background and to motivate our long-term plan of empirical research including brain and robotic sciences following the principles of epigenetic robotics

Problem-based leadership: nurturing managers during turbulent times

Purpose – The paper explores problem-based learning (PBL) as a useful methodology in leadership development during turbulent times. It identifies several pertinent action points for managers to lead through problems while understanding their capacity to empower themselves and others to face challenges at work. Design/methodology/approach – Broad concepts of PBL are used to distil the characteristics of this methodology and how they might be applicable to leadership development. An actual case of PBL in leadership education and training is employed to illustrate the processes of problem solving and reflective action-taking. Findings – When confronted by problems, managers should adopt a learning-oriented mindset and draw on the strengths of others to generate immediate solutions for experimentation. In doing so, they need to accept failure as a prerequisite for creative tensions to be generated and applied in messy circumstances. Until they think out of the box, they will continue to solve problems in tried-and-tested ways obstructing the emergence of revolutionary solutions. Practical implications – In order for managers to make an impact on organizational process and improvement, they need to focus on the action and learn components of PBL. They should be given the space to listen to their own “voice” and internalize the “voice” of others through reflection and dialogue. They should also be recognized for their courage and boldness in confronting problems even if more problems are generated in the process. It is facing the goliath that managers truly grow to become real leaders. Originality/value – Although the concept of PBL has been around for a long while, its applicability to leadership development has not been sufficiently explored in both theory and practice. This paper brings another dimension to the common idea of problem solving where solution seeking is not an end it itself. At best, it is a means to discovering the potential of true leadership in those whose mindset is focused on learning and reflective decision-making

Visual Concepts and Compositional Voting

It is very attractive to formulate vision in terms of pattern theory \cite{Mumford2010pattern}, where patterns are defined hierarchically by compositions of elementary building blocks. But applying pattern theory to real world images is currently less successful than discriminative methods such as deep networks. Deep networks, however, are black-boxes which are hard to interpret and can easily be fooled by adding occluding objects. It is natural to wonder whether by better understanding deep networks we can extract building blocks which can be used to develop pattern theoretic models. This motivates us to study the internal representations of a deep network using vehicle images from the PASCAL3D+ dataset. We use clustering algorithms to study the population activities of the features and extract a set of visual concepts which we show are visually tight and correspond to semantic parts of vehicles. To analyze this we annotate these vehicles by their semantic parts to create a new dataset, VehicleSemanticParts, and evaluate visual concepts as unsupervised part detectors. We show that visual concepts perform fairly well but are outperformed by supervised discriminative methods such as Support Vector Machines (SVM). We next give a more detailed analysis of visual concepts and how they relate to semantic parts. Following this, we use the visual concepts as building blocks for a simple pattern theoretical model, which we call compositional voting. In this model several visual concepts combine to detect semantic parts. We show that this approach is significantly better than discriminative methods like SVM and deep networks trained specifically for semantic part detection. Finally, we return to studying occlusion by creating an annotated dataset with occlusion, called VehicleOcclusion, and show that compositional voting outperforms even deep networks when the amount of occlusion becomes large.Comment: It is accepted by Annals of Mathematical Sciences and Application

Fenomenologia e Cognitive Vision

Vernon (2006) suggerisce di individuare un consenso in Cognitive Vision nella ricerca di capacità e attributi non-funzionali per un sistema robusto e adattivo. Questo contributo presenta una teoria informale di capacità percettive e motorie corrispondenti alle proprietà spaziali fenomeniche degli oggetti, vale a dire ai percetti la cui struttura è studiata in fenomenologia della percezione. Infine, se ne illustrano alcune implicazioni rispetto alle teorie cognitiviste e sensomotorie

非拘束状態動物のナビゲーション行動を計測及び推定するためのビジョンシステム

要約のみTohoku University橋本浩一課