Name
Abstract | ||
|---|---|---|
This work presents a retrieval pipeline and evaluation scheme for the problem of finding the last appearance of personal objects in a large dataset of images captured from a wearable camera. Each personal object is modelled by a small set of images that define a query for a visual search engine.The retrieved results are reranked considering the temporal timestamps of the images to increase the relevance of the later detections. Finally, a temporal interleaving of the results is introduced for robustness against false detections. The Mean Reciprocal Rank is proposed as a metric to evaluate this problem. This application could help into developing personal assistants capable of helping users when they do not remember where they left their personal belongings. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1145/2983576.2983582 | LTA@MM |
DocType | Volume | Citations |
Conference | abs/1608.08139 | 2 |
PageRank | References | Authors |
0.41 | 17 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cristian Reyes | 1 | 2 | 0.41 |
| Eva Mohedano | 2 | 55 | 6.81 |
| McGuinness Kevin | 3 | 314 | 36.70 |
| Noel E. O'Connor | 4 | 2137 | 223.20 |
| Xavier Giró | 5 | 288 | 32.23 |