Concept

Video content analysis

Publications associées (68)

Coronal jets identification using Deep Learning as Image and Video Object Detection

This report presents a study on the development and application of a Region-based Convolutional Neural Network, Faster RCNN and a more complex one, TransVOD, to locate solar coronal jets using data from the Solar Dynamic Observatory (SDO). The study focus ...

2024

Inverse Reinforcement Learning of Pedestrian-Robot Coordination

Aude Billard, David Julian Gonon

We apply inverse reinforcement learning (IRL) with a novel cost feature to the problem of robot navigation in human crowds. Consistent with prior empirical work on pedestrian behavior, the feature anticipates collisions between agents. We efficiently learn ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Encoder-Decoder Models for Human Segmentation and Motion Analysis

Isinsu Katircioglu

Detecting people from 2D images and analyzing their motion in 3D have been long standing computer vision problems central to numerous applications such as autonomous driving and athletic training. Recently, with the availability of large amounts of trainin ...

EPFL2022

How Asynchronous Events Encode Video

Martin Vetterli, Adam James Scholefield, Karen Adam

As event-based sensing gains in popularity, theoretical understanding is needed to harness this technology’s potential. Instead of recording video by capturing frames, event-based cameras have sensors that emit events when their inputs change, thus encodin ...

IEEE2021

Tampered Speaker Inconsistency Detection with Phonetically Aware Audio-visual Features

Sébastien Marcel

The recent increase in social media based propaganda, i.e., ‘fake news’, calls for automated methods to detect tampered content. In this paper, we focus on detecting tampering in a video with a person speaking to a camera. This form of manipulation is easy ...

2019

UAV-Based Situational Awareness System Using Deep Learning

Wenlong Deng

Situational awareness by Unmanned Aerial Vehicles (UAVs) is important for many applications such as surveillance, search and rescue, and disaster response. In those applications, detecting and locating people and recognizing their actions in near real-time ...

2019

Real-time high-resolution omnidirectional imaging platform for drone detection and tracking

Jean-Philippe Thiran, Selman Ergünay, Yusuf Leblebici, Vladan Popovic, Bilal Demir, Gökçen Nurlu

Drones have become steadily affordable, which raises privacy and security concerns as well as interest in drone detection systems. On the other hand, drone detection is a challenging task due to small dimensions of drones, difficulty of long-distance detec ...

SPRINGER HEIDELBERG2019

Light Field Synthesis Using Inexpensive Surveillance Camera Systems

We present a light field synthesis technique that achieves accurate reconstruction given a low-cost, wide-baseline camera rig. Our system integrates optical flow with methods for rectification, disparity estimation, and feature extraction, which we then fe ...

2019

WatchNet: Efficient and Depth-based Network for People Detection in Video Surveillance Systems

Jean-Marc Odobez, Olivier Canévet, Michael Villamizar

We propose a deep-learning approach for people detection on depth imagery. The approach is designed to be deployed as an autonomous appliance for identifying people attacks and intrusion in video surveillance scenarios. To this end, we propose a fully-conv ...

IEEE2018

LF-Net: Learning Local Features from Images

Pascal Fua, Kwang Moo Yi, Eduard Trulls Fortuny, Yuki Ono

We present a novel deep architecture and a training strategy to learn a local feature pipeline from scratch, using collections of images without the need for human supervision. To do so we exploit depth and relative camera pose cues to create a virtual tar ...

2018

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search