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People counting is a challenging task with many applications. We propose a method with a fixed stereo camera that is based on projecting a template onto the depth image. The method was tested on a challenging outdoor dataset with good results and runs in real time.
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This paper describes the work that is done by a group of I3 students at Philips CFT in Eindhoven, Netherlands. I3 is an initiative of Fontys University of Professional Education also located in Eindhoven. The work focuses on the use of computer vision in motion control. Experiments are done with several techniques for object recognition and tracking, and with the guidance of a robot movement by means of computer vision. These experiments involve detection of coloured objects, object detection based on specific features, template matching with automatically generated templates, and interaction of a robot with a physical object that is viewed by a camera mounted on the robot.
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This article deals with automatic object recognition. The goal is that in a certain grey-level image, possibly containing many objects, a certain object can be recognized and localized, based upon its shape. The assumption is that this shape has no special characteristics on which a dedicated recognition algorithm can be based (e.g. if we know that the object is circular, we could use a Hough transform or if we know that it is the only object with grey level 90, we can simply use thresholding). Our starting point is an object with a random shape. The image in which the object is searched is called the Search Image. A well known technique for this is Template Matching, which is described first.
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The Sport Empowers Disabled Youth 2 (SEDY2) project encourages inclusion and equal opportunities in sport for youth with a disability by raising their sports and exercise participation in inclusive settings. The SEDY2 Collection of Inclusion Best Practices report contains good examples of inclusion on youth with a disability in sport at the community and institutional level. This report includes a detailed description of the process of building and using the SEDY2 approach for collection international best practices in sport, the criteria and template used to collect the SEDY2 best practices and the list of SEDY2 international best practices on inclusion in sport for youth with a disability.
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A transition from a linear economy to a more sustainable and circular economy requires different business models. In this chapter, we provide you with an introduction to the nature and logic of business models. In essence, a business model is a description of how value creation between parties or partners is organized, at a particular moment, in a specific context, and given available resources. Conventional business modelling approaches have several weaknesses---the main point of criticism being their focus on creating financial value. With the Business Model Template (BMT), we try to resolve most of these criticisms. To do so we introduce three archetypal business models: the platform, community, and circular economy business models. This chapter provides an overview on how, over three stages and ten building blocks that together make up the Business Model Template, these archetypal business models will be used.
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In this paper, we address the problem of people detection and tracking in crowded scenes using range cameras. We propose a new method for people detection and localisation based on the combination of background modelling and template matching. The method uses an adaptive background model in the range domain to characterise the scene without people. Then a 3D template is placed in possible people locations by projecting it in the background to reconstruct a range image that is most similar to the observed range image. We tested the method on a challenging outdoor dataset and compared it to two methods that each shares one characteristic with the proposed method: a similar template-based method that works in 2D and a well-known baseline method that works in the range domain. Our method performs significantly better, does not deteriorate in crowded environments and runs in real time.
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Within NHL Stenden University of Applied Science, a choice for a new virtual learning environment was made in mid-2021, primarily on policy and management grounds. Early in the migration process, it became clear that this approach could perturb the further rollout of the Design-Based Education (DBE, https://edu.nl/mwp8j) educational concept. Four templates were developed to intertwine technological and educational processes that structure different ways of "blended" learning and teaching within DBE. Initial user experiences show that the templates’ structures help teachers reconsider online learning activities to shape and facilitate blended DBE learning processes.
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