Multiple Feature Fusion Based on Co-Training Approach and Time Regularization for Place Classification in Wearable Video
The analysis of video acquired with a wearable camera is a challenge that multimedia community is facing with the proliferation of such sensors in various applications. In this paper, we focus on the problem of automatic visual place recognition in a weakly constrained environment, targeting the ind...
Saved in:
Main Authors: | Vladislavs Dovgalecs, Rémi Mégret, Yannick Berthoumieu |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2013-01-01
|
Series: | Advances in Multimedia |
Online Access: | http://dx.doi.org/10.1155/2013/175064 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Superpixel guided spectral-spatial feature extraction and weighted feature fusion for hyperspectral image classification with limited training samples
by: Yao Li, et al.
Published: (2025-01-01) -
Motion Feature Retrieval in Basketball Match Video Based on Multisource Motion Feature Fusion
by: Biao Ma, et al.
Published: (2022-01-01) -
Multiple-Wearable-Sensor-Based Gait Classification and Analysis in Patients with Neurological Disorders
by: Wei-Chun Hsu, et al.
Published: (2018-10-01) -
Towards unbiased skin cancer classification using deep feature fusion
by: Ali Atshan Abdulredah, et al.
Published: (2025-01-01) -
The Role and Place of Fusionism in School Geometry Education
by: G. A. Klekovkin
Published: (2015-01-01)