Essays about: "Modal fusion"

Showing result 1 - 5 of 8 essays containing the words Modal fusion.

1. 1. Movement Estimation with SLAM through Multimodal Sensor Fusion

   University essay from Linköpings universitet/Medie- och Informationsteknik; Linköpings universitet/Tekniska fakulteten

   Author : Jimmy Cedervall Lamin; [2024]
   Keywords : slam; discrete-slam; continuous-slam; synchronous; asynchronous; computer vision; BRISK; opencv; ceres; visual; inertial; sensor fusion; multimodal; Simultaneous Localization and Mapping; time offset; pose estimation; quaternions; movement estimation;

   Abstract : In the field of robotics and self-navigation, Simultaneous Localization and Mapping (SLAM) is a technique crucial for estimating poses while concurrently creating a map of the environment. Robotics applications often rely on various sensors for pose estimation, including cameras, inertial measurement units (IMUs), and more. READ MORE

3. 2. Robust Multi-Modal Fusion for 3D Object Detection : Using multiple sensors of different types to robustly detect, classify, and position objects in three dimensions.

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Viktor Kårefjärd; [2023]
   Keywords : Computer Vision; 3D Object Detection; Multi-Modal Fusion; Deep Learning; Datorseenden; 3D-objektdetektion; Multimodal fusion; Djupinlärning;

   Abstract : The computer vision task of 3D object detection is fundamentally necessary for autonomous driving perception systems. These vehicles typically feature a multitude of sensors, such as cameras, radars, and light detection and ranging sensors. READ MORE

4. 3. A real-time Multi-modal fusion model for visible and infrared images : A light-weight and real-time CNN-based fusion model for visible and infrared images in surveillance

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Jin Wanqi; [2023]
   Keywords : Image fusion; deep learning; surveillance; CNN; real time; Bildfusion; djupinlärning; övervakning; CNN; realtid;

   Abstract : Infrared images could highlight the semantic areas like pedestrians and be robust to luminance changes, while visible images provide abundant background details and good visual effects. Multi-modal image fusion for surveillance application aims to generate an informative fused images from two source images real-time, so as to facilitate surveillance observatory or object detection tasks. READ MORE

5. 4. Probabilistic Multi-Modal Data Fusion and Precision Coordination for Autonomous Mobile Systems Navigation : A Predictive and Collaborative Approach to Visual-Inertial Odometry in Distributed Sensor Networks using Edge Nodes

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Isabella Luppi; [2023]
   Keywords : Distributed Sensor Networks; Point Cloud Processing; Bounding Box Fitting; Trajectory Tracking; Distributed Estimation; Predictive Estimation; Edge-Computing; Reti di Sensori Distribuiti; Elaborazione di Nuvole di Punti; Riquadri di Delimitazione; Tracciamento della Traiettoria; Stima Distribuita; Stima Predittiva; Calcolo Distribuito.; Distribuerade Sensornätverk; Bearbetning av Punktmoln; Anpassning av Begränsningsruta; Trajektorieuppföljning; Distribuerad Uppskattning; Prediktiv Uppskattning; Edge-datorbehandling;

   Abstract : This research proposes a novel approach for improving autonomous mobile system navigation in dynamic and potentially occluded environments. The research introduces a tracking framework that combines data from stationary sensing units and on-board sensors, addressing challenges of computational efficiency, reliability, and scalability. READ MORE

6. 5. Multimodal Machine Learning in Human Motion Analysis

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Jia Fu; [2022]
   Keywords : Multimodal machine learning; Modal fusion; Human motion classification; Multimodal maskininlärning; Modal fusion; Mänsklig rörelseklassificering;

   Abstract : Currently, most long-term human motion classification and prediction tasks are driven by spatio-temporal data of the human trunk. In addition, data with multiple modalities can change idiosyncratically with human motion, such as electromyography (EMG) of specific muscles and respiratory rhythm. READ MORE