Idea Competitions under scrutiny: Acquisition, intelligence or public relations mechanism?

Idea Competitions (ICs) are becoming a popular mechanism chosen by firms to perform Open Innovation. They are a way to engage with external sources of knowledge such as individual entrepreneurs and small firms who are asked to submit ideas and compete for a prize. However, little is known about the success of ICs as acquisition mechanisms. The researchers conducted interviews in five multinational companies to evaluate the effects of using ICs as an acquisition mechanism. Although still preliminary, the results of this study show that the success of ICs as an acquisition mechanism remains uncertain because their output (i.e. the number of ideas acquired) is often low compared to the input (i.e. the number of ideas submitted) and effort required to run them (e.g. to vet ideas). Across the cases observed, ICs appear to be more successful at identifying and acquiring early-stage ideas, particularly those outside the current business focus. The study shows that ICs deliver other functional benefits such as improved intelligence and public relations and that these need to be considered as part of the evaluation of the IC's success. The paper concludes by discussing the conditions in which ICs are implemented and the implications for Open Innovation theory. © 2013 Elsevier Inc.

Multi scale shape index for 3D object recognition

We present Multi Scale Shape Index (MSSI), a novel feature for 3D object recognition. Inspired by the scale space filtering theory and Shape Index measure proposed by Koenderink & Van Doorn [6], this feature associates different forms of shape, such as umbilics, saddle regions, parabolic regions to a real valued index. This association is useful for representing an object based on its constituent shape forms. We derive closed form scale space equations which computes a characteristic scale at each 3D point in a point cloud without an explicit mesh structure. This characteristic scale is then used to estimate the Shape Index. We quantitatively evaluate the robustness and repeatability of the MSSI feature for varying object scales and changing point cloud density. We also quantify the performance of MSSI for object category recognition on a publicly available dataset. © 2013 Springer-Verlag.

Obtaining the shape of a moving object with a specular surface

This paper addresses the basic problem of recovering the 3D surface of an object that is observed in motion by a single camera and under a static but unknown lighting condition. We propose a method to establish pixelwise correspondence between input images by way of depth search by investigating optimal subsets of intensities rather than employing all the relevant pixel values. The thrust of our algorithm is that it is capable of dealing with specularities which appear on the top of shading variance that is caused due to object motion. This is in terms of both stages of finding sparse point correspondence and dense depth search. We also propose that a linearised image basis can be directly computed by the procudure of finding the correspondence. We illustrate the performance of the theoretical propositions using images of real objects. © 2009. The copyright of this document resides with its authors.