3D Kinematics Estimation with Biomechanics Model

Human 3D kinematics estimation involves measuring joint angles and body segment scales to quantify and analyze the mechanics of human movements. It has applications in areas such as injury prevention, disease identification, and sports science. Conventional marker-based motion capture methods are expensive both in terms of financial investment...

Benchmarking Data and Computational Efficiency of ActionFormer on Temporal Action Localization Tasks: Analysing the Performance and Generalizability of ActionFormer in Resource-constrained Environments

In temporal action localization, given an input video, the goal is to predict which actions it contains, where they begin and where they end. Training and testing current state-of-the-art, deep learning models is done assuming access to large amounts of data and computational power. Gathering such data is however a challenging task and access to...

Efficient Video Action Recognition: How well does TriDet perform and generalize in a limited compute power and data setting?

In temporal action localization, given an input video, the goal is to predict the action that is present in the video, along with its temporal boundaries. Several powerful models have been proposed throughout the years, with transformer-based models achieving state-of-the-art performance in the recent months. Although novel models are becoming...

Efficient Temporal Action Localization model development practices: A review and analysis of models and a guide of best methods

Temporal Action Localization (TAL) is an important problem in computer vision with uses in video surveillance and recommendation, healthcare, entertainment, and human-computer interaction. Being an inherently data-heavy process, TAL has been bound by the availability of computing power, resulting in its slow pace of innovation. This work aims to...

Efficient Temporal Action Localization via Vision-Language Modelling: An Empirical Study on the STALE Model's Efficiency and Generalizability in Resource-constrained Environments

Temporal Action Localization (TAL) aims to localize the start and end times of actions in untrimmed videos and classify the corresponding action types. TAL plays an important role in understanding video. Existing TAL approaches heavily rely on deep learning and require large-scale data and expensive training processes. Recent advances in...

TemporalMaxer Performance in the Face of Constraint: A Study in Temporal Action Localization: A Comprehensive Analysis on the Adaptability of TemporalMaxer in Resource-Scarce Environments

This paper presents an analysis of the data and compute efficiency of the TemporalMaxer deep learning model in the context of temporal action localization (TAL), which involves accurately detecting the start and end times of specific video actions. The study explores the performance and scalability of the TemporalMaxer model under limited...

Graph database watermarking using pseudo nodes

Although digital watermarking has been a well-researched topic for the past decades and has seen numerous implementations for relational databases, it still lacks research for non-relational schema-less databases. In this paper, we explore proposed techniques for non-relational database watermarking and introduce an improved technique for NoSQL...

Detect the watermark through the training model: A watermarking scheme to protect numerical classification datasets

Datasets play an important role in machine learning technology. The quality of a machine learning model is highly dependent on the quality of the training dataset. Datasets are of great economic value and should be viewed as intellectual property. To protect the property rights of machine learning training datasets, we can make use of the...

Image watermarking for Machine Learning datasets: Using SVD based image watermarking techniques to watermark numerical ML datasets

The media watermarking technique domain has had the last 30 years to develop itself. The non-media side, however, is a way newer sub-domain. [1] The data-gathering process for machine learning algorithms is a tedious and time consuming task. This becomes worse as the scale of these algorithms increases. Thus, protecting the datasets against...

No-Reference Point Cloud Quality Assessment: Feature Relevance Assessment for No-Reference Quality Assessment of 3D Point Cloud Data

The need to capture environments and objects in 3 dimensions to produce a high quality digital representation is proving to be useful in many applications in the world, where there is an increasing dependence on digital spaces. Point Clouds are a data type to represent 3D objects and scenes. During the processing of the point cloud data,...

Eases and Difficulties of Talking to a Virtual Coach for Quitting Smoking and Becoming More Physically Active: A Mixed-Methods Analysis

As the awareness of the risks of smoking tobacco increased, usage declined as people started to attempt to quit smoking more. Currently, a wide variety of mobile health (mHealth) applications focused on smoking cessation exist, however users commonly quit these applications over time. In the case of Sam, a conversational agent that plays the...

Reasons to continue or stop using a virtual coach for quitting smoking and increasing physical activity: A mixed-methods analysis

The increase in health problems due to smoking or lack of physical activity has created the incentive to develop a virtual coach to help people with smoking cessation and increase physical activity. In this study, a mixed-methods analysis (thematic analysis, quantitative analysis, and a literature study) was carried out to find out what the...

Acceptance of a Virtual Coach as Guided Intervention for Smoking Cessation: A Mixed-Methods Analysis

As guided interventions are seen as more effective compared to unguided interventions and because the use of eHealth applications is rising over the years, the need to study the effects of a virtual coach as a substitute for guided interventions was created. A virtual coach does not cost as much time and money as a real coach and would thus be...

Acceptance of a virtual coach for quitting smoking and becoming more physically active: A thematic analysis: Traits for a virtual coach to be a ”friend”

Seeing the virtual coach as a friend is beneficial as it increases the motivation, confidence, and perseverance of the accompanying. Here, an investigation has taken place to what characteristics the virtual coach must possess to establish this friendly relationship. Thus, the main research question is: What are the reasons for seeing the...

Reasons to Be Satisfied or Dissatisfied With a Virtual Coach for Quitting Smoking and Becoming More Physically Active: A Mixed-Methods Analysis

A virtual coach, Sam, was created by the Perfect Fit project to aid users in establishing a foundation to stop smoking via the means of making them more physically active. Data from 500 users had been collected from them during stages which start with a pre-screening phase until a post-questionnaire phase. In the latter stage, they provided a...