People Detection and Analysis Using Depth Sensors
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Electronic Sensors".
Deadline for manuscript submissions: closed (1 March 2022) | Viewed by 3575
Special Issue Editors
Interests: computer vision; deep learning; vision based HCI; IoT
Special Issues, Collections and Topics in MDPI journals
Interests: computer vision; deep learning; face analysis; biometrics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are witnessing the wide diffusion of active depth sensors that represent an effective and affordable solution to capture 3D information even in low-light conditions. At the same time, computer vision and machine learning communities proposed new solutions to process depth data, individually or fused with other information such as RGB images. However, the generalization capabilities and performance of the deep learning models based on depth data, such as a depth map and its related data representations (e.g., normal images, voxels, and point clouds) have not yet been fully investigated. In this context, several challenging problems can be addressed, such as the reliable detection of people, the 3D analysis of humans in terms of body pose, and face and hand analysis, also oriented for the human–computer interaction and biometrics.
This Special Issue will publish innovative work that explores hardware and software solutions for exploiting depth information, investigating the use of ad hoc deep learning models and specific data pre-processing and normalization procedures. The particular topics of interest include, but are not limited to the following:
- people (and face) detection;
- human body pose estimation and refinement;
- people tracking;
- head pose estimation;
- face recognition and verification;
- face analysis;
- action recognition;
- gait analysis;
- human–computer interaction;
- hand detection;
- hand pose estimation;
- gesture recognition;
- depth-based data representations
Prof. Dr. Roberto Vezzani
Dr. Guido Borghi
Guest Editors
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Keywords
- RGB-D computer vision
- depth sensors
- depth maps
- 3D pose estimation and tracking
- 3D body analysis
- applications of 3D vision (human–computer interaction, robotics, etc.)
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