@InProceedings{8081544,
  author = {H. Sabirin and S. Naito},
  booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},
  title = {Two-layer tracking for occlusion handling and inter-sensor identification in multiple depth sensorsbased object detection and tracking},
  year = {2017},
  pages = {1922-1926},
  abstract = {The main challenge in depth-based object detection and tracking process is to provide correct identification of the detected objects during occlusion. This is because the information necessary to distinguish and consequently identify the objects throughout the occlusion events are limited, compared to conventional, color-based object tracking. In this paper we propose a two-layer tracking method that enables automatic occlusion handling and inter-sensor identification for object detection and tracking that utilizes more than one depth sensor. On the first layer, the tracking is first performed independently for each sensor to extract objects' feature and perform initial tracking with separation of the occluded objects. On the second layer, the tracking is performed in the perspective projection of the objects tracked on the first layer that are combined in a single processing plane to provide correct identification of the objects that are detected in one sensor to another. Experiment results show that the proposed method can correctly identified occluded objects and objects that are moving between sensors coverage area.},
  keywords = {feature extraction;image colour analysis;image sensors;object detection;object tracking;sensor fusion;occlusion events;two-layer tracking method;automatic occlusion handling;inter-sensor identification;object tracking process;multiple depth sensors-based object detection;color-based object tracking;object feature extraction;object identification;surveillance;object detection and tracking;depth data;depth-based separation;range sensor},
  doi = {10.23919/EUSIPCO.2017.8081544},
  issn = {2076-1465},
  month = {Aug},
}

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This is because the information necessary to distinguish and consequently identify the objects throughout the occlusion events are limited, compared to conventional, color-based object tracking. In this paper we propose a two-layer tracking method that enables automatic occlusion handling and inter-sensor identification for object detection and tracking that utilizes more than one depth sensor. On the first layer, the tracking is first performed independently for each sensor to extract objects' feature and perform initial tracking with separation of the occluded objects. On the second layer, the tracking is performed in the perspective projection of the objects tracked on the first layer that are combined in a single processing plane to provide correct identification of the objects that are detected in one sensor to another. 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Naito},\n booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},\n title = {Two-layer tracking for occlusion handling and inter-sensor identification in multiple depth sensorsbased object detection and tracking},\n year = {2017},\n pages = {1922-1926},\n abstract = {The main challenge in depth-based object detection and tracking process is to provide correct identification of the detected objects during occlusion. This is because the information necessary to distinguish and consequently identify the objects throughout the occlusion events are limited, compared to conventional, color-based object tracking. In this paper we propose a two-layer tracking method that enables automatic occlusion handling and inter-sensor identification for object detection and tracking that utilizes more than one depth sensor. 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