Recovering 6D Object Pose and Predicting Next-Best-View in the Crowd

Object detection and 6D pose estimation in the crowd (scenes with multiple object instances, severe foreground occlusions and background distractors), has become an important problem in many rapidly evolving technological areas such as robotics and augmented reality. Single shot-based 6D pose estimators with manually designed features are still unable to tackle the above challenges, motivating the research towards unsupervised feature learning and next-best-view estimation. In this work, we present a complete framework for both single shot-based 6D object pose estimation and next-best-view prediction based on Hough Forests, the state of the art object pose estimator that performs classification and regression jointly. Rather than using manually designed features we a) propose an unsupervised feature learnt from depth-invariant patches using a Sparse Autoencoder and b) offer an extensive evaluation of various state of the art features. Furthermore, taking advantage of the clustering performed in the leaf nodes of Hough Forests, we learn to estimate the reduction of uncertainty in other views, formulating the problem of selecting the next-best-view. To further improve pose estimation, we propose an improved joint registration and hypotheses verification module as a final refinement step to reject false detections. We provide two additional challenging datasets inspired from realistic scenarios to extensively evaluate the state of the art and our framework. One is related to domestic environments and the other depicts a bin-picking scenario mostly found in industrial settings. We show that our framework significantly outperforms state of the art both on public and on our datasets.Comment: CVPR 2016 accepted paper, project page: http://www.iis.ee.ic.ac.uk/rkouskou/6D_NBV.htm

Determinants of cooperation with institutional partners and innovation - performance of Polish manufacturing enterprises. Research outcomes

The aim of this paper is to assess of the influence of institutional cooperation (with research institutes and universities) on the innovation performance of companies as well as determinants of such cooperation. The analysis was based on data from the Polish version of the Community Innovation Survey (CIS) for 2008-2010. The sample consists of 7783 medium-sized and large manufacturing enterprises from sections C to E. Based on the results of a structural equation model it has been concluded that there is a statistically significant relation between institutional cooperation and innovation performance of the researched companies, as well as (in the case of cooperation with Polish companies) in the introduction of product innovations new for the country, Europe or the world. The analysis of critical values between parameters enables the establishment of a hierarchy of company features which determines such cooperation. These include the system of employee incentives for the creation of intellectual property, company size and own R&D -department. The application of the employee incentive system better explains the decision to establish cooperation with Polish companies than with foreign ones. However a feature which is not institutional cooperation friendly is belonging to a larger group of companies. Key words: institutional cooperation, innovation -performance, Polish CIS, PolandPreparation and printing funded by the National Agency for Research and Development under project “Kreator Innowacyjności – wparcie dla Przedsiębiorczości akademickiej

Improving 6D Pose Estimation of Objects in Clutter via Physics-aware Monte Carlo Tree Search

This work proposes a process for efficiently searching over combinations of individual object 6D pose hypotheses in cluttered scenes, especially in cases involving occlusions and objects resting on each other. The initial set of candidate object poses is generated from state-of-the-art object detection and global point cloud registration techniques. The best-scored pose per object by using these techniques may not be accurate due to overlaps and occlusions. Nevertheless, experimental indications provided in this work show that object poses with lower ranks may be closer to the real poses than ones with high ranks according to registration techniques. This motivates a global optimization process for improving these poses by taking into account scene-level physical interactions between objects. It also implies that the Cartesian product of candidate poses for interacting objects must be searched so as to identify the best scene-level hypothesis. To perform the search efficiently, the candidate poses for each object are clustered so as to reduce their number but still keep a sufficient diversity. Then, searching over the combinations of candidate object poses is performed through a Monte Carlo Tree Search (MCTS) process that uses the similarity between the observed depth image of the scene and a rendering of the scene given the hypothesized pose as a score that guides the search procedure. MCTS handles in a principled way the tradeoff between fine-tuning the most promising poses and exploring new ones, by using the Upper Confidence Bound (UCB) technique. Experimental results indicate that this process is able to quickly identify in cluttered scenes physically-consistent object poses that are significantly closer to ground truth compared to poses found by point cloud registration methods.Comment: 8 pages, 4 figure

Do Government Policies Foster Environmental Performance of Enterprises from CEE Region?

In recent years, EU countries, including these from the Central Eastern European (CEE) region has recognised, that eco-innovation should be treated as strategic priority of their economies. The aim of this paper is to present a cross-country analysis of the connection between eco-innovation and its main drivers within firms from selected CEE countries (Bulgaria, Czech Republic, Romania) and Germany. The empirical part is based on micro-data for Community Innovation Survey (CIS) 2006-2008. Based on the results of stepwise regression between main policy actions sustaining innovation activity and eco-innovation performance we can conclude, that financial support for innovation activities has a rather limited role in promoting eco-innovation. At the same time enterprises from the CEE region regard environmental regulations as the most important drivers of eco-innovation. In Germany, a country ranked in the highest category in the Eco-Innovation Scoreboard, the variety of forces that influence eco-innovation is much more wide-ranging. This indicates that government actions should take a broader look and lay the more general bases fostering the model of a green growth

The influence of social value and selfcongruity on interpersonal connections in virtual social networks by Gen-Y tourists

This research focuses on the relationship of self-congruity and perceived social value with the interpersonal connections established by Generation Y tourists in virtual social networks. A quantitative study was performed using a sample of young travelers from Spain. The methodologies of Confirmatory Factor Analysis (CFA) and Structural Equation Models (SEM) were used to analyze the results. The findings of the research show that self-congruity influences the perceived social value; the perceived social value leads to satisfaction and the creation of interpersonal connections in virtual social networks; and the interpersonal connections in virtual social networks influence the use of these tools by Generation Y travelers

Robust Multiple Lane Road Modeling Based on Perspective Analysis

Road modeling is the first step towards environment perception within driver assistance video-based systems. Typically, lane modeling allows applications such as lane departure warning or lane invasion by other vehicles. In this paper, a new monocular image processing strategy that achieves a robust multiple lane model is proposed. The identification of multiple lanes is done by firstly detecting the own lane and estimating its geometry under perspective distortion. The perspective analysis and curve fitting allows to hypothesize adjacent lanes assuming some a priori knowledge about the road. The verification of these hypotheses is carried out by a confidence level analysis. Several types of sequences have been tested, with different illumination conditions, presence of shadows and significant curvature, all performing in realtime. Results show the robustness of the system, delivering accurate multiple lane road models in most situations

Co-operation and economic relationship as determinants for competitiveness in the food sector: the Spanish wheat to bread chain

The objective of the paper is to investigate the impact of co-operation amongst stakeholders of the food chain on enterprise competitiveness. The analysis focuses on the Spanish wheat to bread chain. A theoretical model is developed which covers the main components that define competitiveness (profitability, turnover, market share, customer loyalty and product quality), quality supply chain relationship (trust, commitment and satisfaction) and the main factors explaining supply chain relationship (i.e. quality and frequency of the communication, personal bounds, etc.). The Spanish wheat to bread supply chain has been chosen to empirically test the model. This sector is very fragmented all along the chain, with a high number of wheat farmers, millers and bakers. Exchanges in the sector are mainly done in the open market but there is an increasing tendency to maintain stable relationships with suppliers to assure quality. Therefore, stakeholders in the wheat to bread chain are mainly using two types of economic relationships: “repeated market transactions” and “spot market” but the former is by far the most used. Based on data from a standardised survey with farmers, processors and retailers a structural equation modelling approach has been applied to empirically test the influence of relationship quality on stakeholders’ competitiveness in the Spanish wheat to bread chain. The main conclusion of the study is that, as the quality of the relationship in the Spanish wheat to bread chain improves the stakeholder’ competitiveness increases. The results also reveal that quality of the relationship in the Spanish wheat to bread chain is based on trust, satisfaction and commitment with buyers/sellers and strongly influenced by communication quality and quantity. In addition, the outcome shows that the quality of communication has an indirect positive effect on stakeholders’ competitiveness through the relationship quality. Finally, the only factor that will influence the quality of the relationship is the equal power distribution along the chain. Moreover, personal bounds positively influence the quality of communication in the bread Spanish supply chain.competitiveness, food, Spain, Agribusiness,