Results 281 to 290 of about 167,485 (300)

Transferring attributes for person re-identification

2015 12th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2015
Person re-identification is an important computer vision task with many applications in areas such as surveillance or multimedia. Approaches relying on handcrafted image features struggle with many factors (e.g. lighting, camera angle) which lead to a large variety in visual appearance for the same individual. Features based on semantic attributes of a
Schumann, Arne, Stiefelhagen, Rainer
openaire   +2 more sources

Taichi distance for person re-identification

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017
Metric learning is an important issue in person re-identification, and Mahalanobis-distance based metric learning methods prevail in this field. All of these approaches can be considered as equivalently projecting all samples to a new metric space and calculating the Euclidean distance there.
Wang, Zheng, Hu, Ruimin, Yu, Yi, Liang, Chao, Chen, Chen   +4 more
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View-Aware Person Re-identification

2019
Appearance-based person re-identification (PRID) is currently an active and challenging research topic. Recently proposed approaches have mostly dealt with low- and middle-level processing of images. Furthermore, there is very limited research that has focused on view information.
Gregor Blott, Jie Yu 0013, Christian Heipke   +2 more
openaire   +1 more source

Active learning for person re-identification

2012 International Conference on Machine Learning and Cybernetics, 2012
Person re-identification is defined as to find the same person who re-occurred in a multi-camera surveillance system. Existing machine learning approaches focus on extracting or learning discriminative features followed by template matching using a distance measure. However, labeling images for a training set is a time consuming task.
openaire   +1 more source

Cross Dataset Person Re-identification

2015
Until now, most existing researches on person re-identification aim at improving the recognition rate on single dataset setting. The training data and testing data of these methods are form the same source. Although they have obtained high recognition rate in experiments, they usually perform poorly in practical applications. In this paper, we focus on
Yang Hu, Dong Yi, Shengcai Liao, Zhen Lei 0001, Stan Z. Li   +4 more
openaire   +1 more source

Learning Person Re-Identification Models From Videos With Weak Supervision

IEEE Transactions on Image Processing, 2021
Xueping Wang, Dripta S Raychaudhuri, Sujoy Paul   +2 more
exaly  

Deep Learning for Person Re-Identification: A Survey and Outlook

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
Mang Ye, Jianbing Shen, Tao Xiang
exaly  

Dual-Stream Guided-Learning via a Priori Optimization for Person Re-identification

ACM Transactions on Multimedia Computing, Communications and Applications, 2021
Junyi Wu, Qiang Wu, Jianqiang Zhao
exaly  

Making person search enjoy the merits of person re-identification

Pattern Recognition, 2022
Chuang Liu, Shibao Zheng
exaly  

Deep features for person re-identification on metric learning

Pattern Recognition, 2021
Dapeng Tao, Jun Cheng
exaly