Search Results for author:
Found 17 papers, 3 papers with code
Crime scene classification from skeletal trajectory analysis in surveillance settings
Next, given the availability of the trajectory-level ground truth, we introduce a trajectory-based crime classification framework.
InstaIndoor and Multi-modal Deep Learning for Indoor Scene Recognition
Furthermore, we highlight the potential of our approach by benchmarking on a YouTube-8M subset of indoor scenes as well, where it achieves 74% accuracy and 0. 74 F1-Score.
Playing to distraction: towards a robust training of CNN classifiers through visual explanation techniques
Unlike the attention mechanisms that focus on the relevant parts of images, we aim to improve the robustness of the model by making it pay attention to other regions as well.
Eating Habits Discovery in Egocentric Photo-streams
Eating habits are learned throughout the early stages of our lives.
Behavioural pattern discovery from collections of egocentric photo-streams
Based on the similarity among the time-frames that describe the collected days for a user, we propose a new unsupervised greedy method to discover the behavioural pattern set based on a novel semantic clustering approach.
Deep learning for scene recognition from visual data: a survey
We first give an overview of available datasets for image and video scene recognition.
Unsupervised routine discovery in egocentric photo-streams
The routine of a person is defined by the occurrence of activities throughout different days, and can directly affect the person's health.
Towards Emotion Retrieval in Egocentric PhotoStream
The availability and use of egocentric data are rapidly increasing due to the growing use of wearable cameras.
Hierarchical approach to classify food scenes in egocentric photo-streams
Recent studies have shown that the environment where people eat can affect their nutritional behaviour.
Towards Egocentric Person Re-identification and Social Pattern Analysis
We propose a model that enables us to evaluate and visualize social traits obtained by analysing social interactions appearance within egocentric photostreams.
Towards Unsupervised Familiar Scene Recognition in Egocentric Videos
Nowadays, there is an upsurge of interest in using lifelogging devices.
On the Role of Event Boundaries in Egocentric Activity Recognition from Photostreams
Event boundaries play a crucial role as a pre-processing step for detection, localization, and recognition tasks of human activities in videos.
MACNet: Multi-scale Atrous Convolution Networks for Food Places Classification in Egocentric Photo-streams
This model is based on a deep end-to-end model for automatic food places recognition by analyzing egocentric photo-streams.
Serious Games Application for Memory Training Using Egocentric Images
Mild cognitive impairment is the early stage of several neurodegenerative diseases, such as Alzheimer's.
R-Clustering for Egocentric Video Segmentation
In this paper, we present a new method for egocentric video temporal segmentation based on integrating a statistical mean change detector and agglomerative clustering(AC) within an energy-minimization framework.
Sentiment Recognition in Egocentric Photostreams
Lifelogging is a process of collecting rich source of information about daily life of people.
SR-Clustering: Semantic Regularized Clustering for Egocentric Photo Streams Segmentation
While wearable cameras are becoming increasingly popular, locating relevant information in large unstructured collections of egocentric images is still a tedious and time consuming processes.
