A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets
نویسندگان
چکیده
منابع مشابه
A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets
Person re-identification (re-id) is a critical problem in video analytics applications such as security and surveillance. The public release of several datasets and code for vision algorithms has facilitated rapid progress in this area over the last few years. However, directly comparing re-id algorithms reported in the literature has become difficult since a wide variety of features, experimen...
متن کاملA Comprehensive Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets
Person re-identification (re-id) is a critical problem in video analytics applications such as security and surveillance. The public release of several datasets and code for vision algorithms has facilitated rapid progress in this area over the last few years. However, directly comparing re-id algorithms reported in the literature has become difficult since a wide variety of features, experimen...
متن کاملMARS: A Video Benchmark for Large-Scale Person Re-Identification
This paper considers person re-identification (re-id) in videos. We introduce a new video re-id dataset, named Motion Analysis and Reidentification Set (MARS), a video extension of the Market-1501 dataset. To our knowledge, MARS is the largest video re-id dataset to date. Containing 1,261 IDs and around 20,000 tracklets, it provides rich visual information compared to image-based datasets. Mean...
متن کاملSaliency Weighted Features for Person Re-identification
In this work we propose a novel person re-identification approach. The solution, inspired by human gazing capabilities, wants to identify the salient regions of a given person. Such regions are used as a weighting tool in the image feature extraction process. Then, such novel representation is combined with a set of other visual features in a pairwise-based multiple metric learning framework. F...
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Recently, many methods of person re-identification (ReID) rely on part-based feature representation to learn a discriminative pedestrian descriptor. However, the spatial context between these parts is ignored for the independent extractor on each separate part. In this paper, we propose to apply Long Short-Term Memory (LSTM) in an end-to-end way to model the pedestrian, seen as a sequence of bo...
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ژورنال
عنوان ژورنال: IEEE Transactions on Pattern Analysis and Machine Intelligence
سال: 2019
ISSN: 0162-8828,2160-9292,1939-3539
DOI: 10.1109/tpami.2018.2807450