We have two midterm master project presentations on Friday, 18 September starting 15:45. The session will be on Zoom.

Presenter: Berend Baas

Title: Latent shape editing

Abstract: In recent years, deep learning on shapes and manifolds has been used to try and perform a variety of tasks, such as classification, deformation transfer and shape matching. This is often done through architectures such as Autoencoders or Generative Adversarial Networks, that try to learn a vector representation of training shapes, which is then used for downstream tasks.

However, current trained representations are generally poorly structured: Their latent space consists of manifolds that are entangled and highly non-linear. This makes it difficult to predict the results of modifications in the latent space on the output of the network. In this work, we investigate the latent space of shape networks, to try and develop techniques to obtain semantic deformations from latent editing operations. We consider two approaches: developing techniques to navigate complex entangles latent spaces, and developing less entangled and more interpretable representations, that can help in providing semantic editing operations.

Presenter: Ruben Vroegindeweij

Title: Depicting motion in a still image by spatio-temporal image fusion

Abstract: TBD

*Zoom meeting details upon request.

You are cordially invited to attend our CG Colloquium on Thursday, March 12th, 2020, 15:45-17:45h, Lecture Hall D@ta (Building 36)

The program features the following two speakers:

Prerak Mody

Title: 3D Human Pose Estimation Using a Top-view Depth Camera

Abstract: Delirium is a cause of concern within the health industry due to many postsurgery patients succumbing to this mental disease which disturbs their path to a full recovery. To understand and detect the onset of delirium within hospital ICU rooms, a depth camera (Microsoft Kinect) is attached to the ceiling. This depth data preserves privacy but also provides an opportunity to analyze the interactions taking place between the various stakeholders such as patient, hospital staff and visiting family. This project is being done at Philips Research, Eindhoven where my task is to extract the 3D human pose of individuals in the rooms. To this end, I extract the 3D point cloud data and run a supervised learning technique (i.e. 3D Convolutional Neural Network) to extract human pose. Having established a baseline, I am now investigating unsupervised and semi-supervised techniques to reduce the data and data annotation requirements respectively.

Thomas Saulou

Title: Photoshop for dummies : Energy-based image modification for photography composition

Abstract: Cameras have almost reached the limits in terms of hardware and optics, computational methods are now the major way to improve a photograph. However, too few tools are developed to enhance image composition. In this project, we introduce new methods based on photography rules to help photographers to modify the picture’s composition. We present a general approach to image deformation based on the energy, and applications of this approach to the problems of photography composition. Our method is inspired from works found in the prior art. The key advantage of our operator is the content-aware deformation function, which optimizes the location of the pixels modification. The operator has been developed to change lines composition in photographs.

You are cordially invited to attend our CG Colloquium on Thursday, February 27th, 2020, 15:45-17:45h, room Kubus (building 26).

Johan van de Koppel, NIOZ

Title: Do self-organized patterns provide a solid basis for building infinite natural landscapes?

Abstract: Natural landscapes, when unaffected by human interference, are often characterized by a bewildering array of repeating natural patterns. Even in landscapes that are as good as flat, as are many dutch ecosystems, regular spatial patterns are found at many scales because of the interactions of organisms with physical forces, a process called spatial self-organization. In this talk, I will discuss how, by combining patterns at multiple spatial scales and including a multitude of processes, we can create visualisations of natural systems that are – in theory – infinite in size, without resorting to noise as the predominant factor creating heterogeneity spatial patterns occurring in the landscape, the ground and in the natural community (i.e. vegetation), we can build CGI representations that are theoretically infinite in scale. I will describe the origin of the patterns, and demonstrate how to build a visualization using patterns at different scales, using intertidal ecosystems as an example.

You are cordially invited to attend our CG Colloquium on Thursday, February 20th, 2020, 15:45-17:45h, room Kubus (building 26).

Jim Whitehead

Title: Procedural Generation Using Linear Constraints

Abstract: Procedural content generation problems sometimes involve systems of linear equality and inequality constraints among the elements being generated. Cassowary is a constraint solver designed for solving these types of constraints at interactive speeds. It is widely used in user interface toolkits, and multiple implementations are available. To date, Cassowary has not been used in procedural content generation. This talk presents Cassowary and gives examples of its use in procedural content generation.

You are cordially invited to attend our CG Colloquium on Thursday, February 13th, 2020, 15:45-17:45h, room Wit licht (building 26).

The program features the following two speakers:

Priyanka Bhaskar

Title: Narcolepsy – Exploratory Analysis

Abstract: Narcolepsy is a chronic neurological condition that results from the dysregulation of the sleep-wake cycle occurring in an early stage, specifically in adolescence. Although Narcolepsy occurs in an early stage there is a delay in diagnosis due to multiple reasons such as lack of symptom recognition, misdiagnoses as some of the symptoms overlap with other disorders like epilepsy, depression, insomnia to name a few. As a result of delayed diagnosis, the overall quality of life of a patient is affected.
The symptom pentad of narcolepsy includes excessive daytime sleepiness, cataplexy, hypnagogic hallucinations, sleep paralysis and disturbed nocturnal sleep. However, the symptoms related to narcolepsy are not limited to the pentad and cover a broad range covering symptoms not directly related to sleep, like, increase in weight, binge eating, anxiety, agitation. In order to reduce the delay in diagnosis, apart from having and creating an awareness about narcolepsy and it’s symptoms, it is important to look beyond the symptom pentad and understand the occurrences and interrelationships between these symptoms. Hence, this project aims at performing an exploratory analysis by looking into 20 symptoms, to understand symptom occurrences, the associations between symptoms to
name a few.

Joost Wooning

Title: Using Augmented Reality to assist in Medical Interventions

Abstract: Augmented Reality (AR) is an upcoming technique which can be used to display images overlaid on the normal vision of the user, several systems are on the market, in this project a Microsoft HoloLens will be used. A possible use of this technology is during medical interventions, allowing a surgeon to see displayed images inside a patient during surgery. If used as guidance a high accuracy of displayed projections is required to prevent damaging tissue. Previous work uses external tracking systems to enable accurate projections, using these systems is however not always possible, therefore this project will only use the hardware on a HoloLens. Previous research has shown that the spatial tracking of the HoloLens is not accurate, markers will, therefore, be used to track positions. The goal is to display a projection based on a CT image of a patient in the corresponding position inside the patient and report how accurate this projection is.