Name
Abstract | ||
|---|---|---|
Kinship verification aims to determine whether two persons are kin related or not. This is an emerging topic in computer vision due to its practical potential applications such as family album management. Most of previous works are based on checking kinship from face patterns and more recently from voices. We provide in this paper the first investigation in the literature on kinship verification from gait. The main purpose is to study whether family members do share some gait patterns. As this is a new topic, we started by collecting a new dataset for kinship verification from human gait containing several pairs of video sequences of celebrities and their relatives. The database will be released to the research community for research purposes. Along with the database, we provide results using baseline methods using silhouette and video based analysis. Moreover, we also propose a two-stream 3D-CNN to tackle the problem. The preliminary experimental results point out the potential usefulness of gait information for kinship verification. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ICIP40778.2020.9190787 | 2020 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) |
Keywords | DocType | ISSN |
Kinship verification, Human gait, 3-D Convolution Neural Network | Conference | 1522-4880 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Salah Eddine Bekhouche | 1 | 0 | 0.34 |
| Abdelhakim Chergui | 2 | 0 | 0.34 |
| Abdenour Hadid | 3 | 3305 | 146.00 |
| Yassine Ruichek | 4 | 0 | 0.34 |