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Model-based Behavioural Tracking and Scale Invariant Features in Omnidirectional Matching

Publications associées (67)

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Test-time adaptation for 6D pose tracking

Andrea Cavallaro

We propose a test -time adaptation for 6D object pose tracking that learns to adapt a pre -trained model to track the 6D pose of novel objects. We consider the problem of 6D object pose tracking as a 3D keypoint detection and matching task and present a mo ...

Elsevier Sci Ltd2024

Diff3DHPE: A Diffusion Model for 3D Human Pose Estimation

Tong Zhang

Accurately estimating 3D human pose (3D HPE) and joint locations using only 2D keypoints is challenging. The noise in the predictions produced by conventional 2D human pose estimators often impeded the accuracy. In this paper, we present a diffusion-based ...

Los Alamitos2023

Training Algorithms for Multiple Object Tracking

Andrii Maksai

Multiple object tracking is a crucial Computer Vision Task. It aims at locating objects of interest in the image sequences, maintaining their identities, and identifying their trajectories over time. A large portion of current research focuses on tracking ...

EPFL2019

On The Move: Localization With Kinetic Euclidean Distance Matrices

Martin Vetterli, Ivan Dokmanic, Puoya Tabaghi

In this paper, we propose kinetic Euclidean distance matrices (KEDMs) a new algebraic tool for localization of moving points from spatio temporal distance measurements. KEDMs are inspired by the well-known Euclidean distance matrices (EDM) which model stat ...

IEEE2019

SIPS: Unsupervised Succinct Interest Points

Davide Scaramuzza, Titus Cieslewski

Detecting interest points is a key component of vision-based estimation algorithms, such as visual odometry or visual SLAM. Classically, interest point detection has been done with methods such as Harris, FAST, or DoG. Recently, better detectors have been ...

2018

Tracking Interacting Objects in Image Sequences

Xinchao Wang

Object tracking in image sequences is a key challenge in computer vision. Its goal is to follow objects that move or evolve over time while preserving the identity of each object. However, most existing approaches focus on one class of objects and model on ...

EPFL2015

Real-Time High-Resolution Multiple-Camera Depth Map Estimation Hardware and Its Applications

Abdulkadir Akin

Depth information is used in a variety of 3D based signal processing applications such as autonomous navigation of robots and driving systems, object detection and tracking, computer games, 3D television, and free view-point synthesis. These applications r ...

EPFL2015

Biologically Inspired Keypoints

Alexandre Massoud Alahi

This chapter describes methods to extract and represent biologically inspired keypoints. It highlights the design choices that are not contradictory to the current understanding of the human visual system (HVS). The chapter briefly defines some terminologi ...

Wiley2015

An inertial sensor-based system for spatio-temporal analysis in classic cross-country skiing diagonal technique

Kamiar Aminian, Julien Favre, Benedikt Fasel, Julien Chardonnens

The present study proposes a method based on ski fixed inertial sensors to automatically compute spatio-temporal parameters (phase durations, cycle speed and cycle length) for the diagonal stride in classical cross-country skiing. The proposed system was v ...

Elsevier2015

Receptive Fields Selection for Binary Feature Description

Pascal Fua, Zhiye Wang, Tomasz Piotr Trzcinski, Bin Fan

Feature description for local image patch is widely used in computer vision. While the conventional way to design local descriptor is based on expert experience and knowledge, learning based methods for designing local descriptor become more and more popul ...

Institute of Electrical and Electronics Engineers2014