The Experts below are selected from a list of 13845 Experts worldwide ranked by ideXlab platform
Thomas S. Huang - One of the best experts on this subject based on the ideXlab platform.
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ICIP - ‘Bag of segments’ for motion Trajectory Analysis
2008 15th IEEE International Conference on Image Processing, 2008Co-Authors: Yue Zhou, Thomas S. HuangAbstract:We propose a novel method to represent motion Trajectory - 'bag of segments'. Motivated by the 'bag of words' approach in text mining and more recently in image categorization, we represent each Trajectory as a collection of segments, each assigned a membership to a codeword of a dictionary. The Trajectory segments are represented by their shape and motion information while the inter-segment relationship is ignored. In the 'bag of Trajectory segments' representation, the trajectories are transformed to a vector in the codeword space. The codebook is generated by clustering a large amount of Trajectory segments using expectation maximization (EM) algorithm and each codeword is a weighted regression model. Given the codebook, trajectories are segmented and associated with a soft-frequency vector in codeword space as an intermediate representation. With the 'bag of segments' representation, Trajectory Analysis can be carried out in vector space as traditional data. Experiments show the 'bag of segments' method is very effective in Trajectory similarity search and classification.
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real time human action recognition by luminance field Trajectory Analysis
ACM Multimedia, 2008Co-Authors: Zhu Li, Yun Fu, Thomas S. HuangAbstract:The explosive growth of video content in recent years fueled by the technological leaps in computing and communication has created new challenges for video content Analysis that can serve applications in video surveillance, video searching and mining. Human action detection and recognition is one of the important tasks in this effort. In this paper, we present a luminance field manifold Trajectory Analysis based solution for human activity recognition, without explicit object level information extraction and understanding. This approach is computationally efficient and can operate in real time. The recognition performance is also comparable with the state of art in comparable set ups.
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‘Bag of segments’ for motion Trajectory Analysis
2008 15th IEEE International Conference on Image Processing, 2008Co-Authors: Yue Zhou, Thomas S. HuangAbstract:We propose a novel method to represent motion Trajectory - 'bag of segments'. Motivated by the 'bag of words' approach in text mining and more recently in image categorization, we represent each Trajectory as a collection of segments, each assigned a membership to a codeword of a dictionary. The Trajectory segments are represented by their shape and motion information while the inter-segment relationship is ignored. In the 'bag of Trajectory segments' representation, the trajectories are transformed to a vector in the codeword space. The codebook is generated by clustering a large amount of Trajectory segments using expectation maximization (EM) algorithm and each codeword is a weighted regression model. Given the codebook, trajectories are segmented and associated with a soft-frequency vector in codeword space as an intermediate representation. With the 'bag of segments' representation, Trajectory Analysis can be carried out in vector space as traditional data. Experiments show the 'bag of segments' method is very effective in Trajectory similarity search and classification.
Jorgen Brandt - One of the best experts on this subject based on the ideXlab platform.
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examining ambrosia pollen episodes at poznan poland using back Trajectory Analysis
International Journal of Biometeorology, 2007Co-Authors: Alicja Stach, Matt Smith, Carsten Ambelas Skjoth, Jorgen BrandtAbstract:The pollen grains of Ambrosia spp. are considered to be important aeroallergens in parts of southern and central Europe. Back-trajectories have been analysed with the aim of finding the likely sources of Ambrosia pollen grains that arrived at Poznan (Poland). Temporal variations in Ambrosia pollen at Poznan from 1995–2005 were examined in order to identify Ambrosia pollen episodes suitable for further investigation using back-Trajectory Analysis. The trajectories were calculated using the transport model within the Lagrangian air pollution model, ACDEP (Atmospheric Chemistry and Deposition). Analysis identified two separate populations in Ambrosia pollen episodes, those that peaked in the early morning between 4 a.m. and 8 a.m., and those that peaked in the afternoon between 2 p.m. and 6 p.m.. Six Ambrosia pollen episodes between 2001 and 2005 were examined using back-Trajectory Analysis. The results showed that Ambrosia pollen episodes that peaked in the early morning usually arrived at Poznan from a southerly direction after passing over southern Poland, the Czech Republic, Slovakia and Hungary, whereas air masses that brought Ambrosia pollen to Poznan during the afternoon arrived from a more easterly direction and predominantly stayed within the borders of Poland. Back-Trajectory Analysis has shown that there is a possibility that long-range transport brings Ambrosia pollen to Poznan from southern Poland, the Czech Republic, Slovakia and Hungary. There is also a likelihood that Ambrosia is present in Poland, as shown by the arrival of pollen during the afternoon that originated primarily from within the country.
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Examining Ambrosia pollen episodes at Poznań (Poland) using back-Trajectory Analysis
International Journal of Biometeorology, 2006Co-Authors: Alicja Stach, Matt Smith, Carsten Ambelas Skjoth, Jorgen BrandtAbstract:The pollen grains of Ambrosia spp. are considered to be important aeroallergens in parts of southern and central Europe. Back-trajectories have been analysed with the aim of finding the likely sources of Ambrosia pollen grains that arrived at Poznan (Poland). Temporal variations in Ambrosia pollen at Poznan from 1995–2005 were examined in order to identify Ambrosia pollen episodes suitable for further investigation using back-Trajectory Analysis. The trajectories were calculated using the transport model within the Lagrangian air pollution model, ACDEP (Atmospheric Chemistry and Deposition). Analysis identified two separate populations in Ambrosia pollen episodes, those that peaked in the early morning between 4 a.m. and 8 a.m., and those that peaked in the afternoon between 2 p.m. and 6 p.m.. Six Ambrosia pollen episodes between 2001 and 2005 were examined using back-Trajectory Analysis. The results showed that Ambrosia pollen episodes that peaked in the early morning usually arrived at Poznan from a southerly direction after passing over southern Poland, the Czech Republic, Slovakia and Hungary, whereas air masses that brought Ambrosia pollen to Poznan during the afternoon arrived from a more easterly direction and predominantly stayed within the borders of Poland. Back-Trajectory Analysis has shown that there is a possibility that long-range transport brings Ambrosia pollen to Poznan from southern Poland, the Czech Republic, Slovakia and Hungary. There is also a likelihood that Ambrosia is present in Poland, as shown by the arrival of pollen during the afternoon that originated primarily from within the country.
Matt Smith - One of the best experts on this subject based on the ideXlab platform.
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examining ambrosia pollen episodes at poznan poland using back Trajectory Analysis
International Journal of Biometeorology, 2007Co-Authors: Alicja Stach, Matt Smith, Carsten Ambelas Skjoth, Jorgen BrandtAbstract:The pollen grains of Ambrosia spp. are considered to be important aeroallergens in parts of southern and central Europe. Back-trajectories have been analysed with the aim of finding the likely sources of Ambrosia pollen grains that arrived at Poznan (Poland). Temporal variations in Ambrosia pollen at Poznan from 1995–2005 were examined in order to identify Ambrosia pollen episodes suitable for further investigation using back-Trajectory Analysis. The trajectories were calculated using the transport model within the Lagrangian air pollution model, ACDEP (Atmospheric Chemistry and Deposition). Analysis identified two separate populations in Ambrosia pollen episodes, those that peaked in the early morning between 4 a.m. and 8 a.m., and those that peaked in the afternoon between 2 p.m. and 6 p.m.. Six Ambrosia pollen episodes between 2001 and 2005 were examined using back-Trajectory Analysis. The results showed that Ambrosia pollen episodes that peaked in the early morning usually arrived at Poznan from a southerly direction after passing over southern Poland, the Czech Republic, Slovakia and Hungary, whereas air masses that brought Ambrosia pollen to Poznan during the afternoon arrived from a more easterly direction and predominantly stayed within the borders of Poland. Back-Trajectory Analysis has shown that there is a possibility that long-range transport brings Ambrosia pollen to Poznan from southern Poland, the Czech Republic, Slovakia and Hungary. There is also a likelihood that Ambrosia is present in Poland, as shown by the arrival of pollen during the afternoon that originated primarily from within the country.
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Examining Ambrosia pollen episodes at Poznań (Poland) using back-Trajectory Analysis
International Journal of Biometeorology, 2006Co-Authors: Alicja Stach, Matt Smith, Carsten Ambelas Skjoth, Jorgen BrandtAbstract:The pollen grains of Ambrosia spp. are considered to be important aeroallergens in parts of southern and central Europe. Back-trajectories have been analysed with the aim of finding the likely sources of Ambrosia pollen grains that arrived at Poznan (Poland). Temporal variations in Ambrosia pollen at Poznan from 1995–2005 were examined in order to identify Ambrosia pollen episodes suitable for further investigation using back-Trajectory Analysis. The trajectories were calculated using the transport model within the Lagrangian air pollution model, ACDEP (Atmospheric Chemistry and Deposition). Analysis identified two separate populations in Ambrosia pollen episodes, those that peaked in the early morning between 4 a.m. and 8 a.m., and those that peaked in the afternoon between 2 p.m. and 6 p.m.. Six Ambrosia pollen episodes between 2001 and 2005 were examined using back-Trajectory Analysis. The results showed that Ambrosia pollen episodes that peaked in the early morning usually arrived at Poznan from a southerly direction after passing over southern Poland, the Czech Republic, Slovakia and Hungary, whereas air masses that brought Ambrosia pollen to Poznan during the afternoon arrived from a more easterly direction and predominantly stayed within the borders of Poland. Back-Trajectory Analysis has shown that there is a possibility that long-range transport brings Ambrosia pollen to Poznan from southern Poland, the Czech Republic, Slovakia and Hungary. There is also a likelihood that Ambrosia is present in Poland, as shown by the arrival of pollen during the afternoon that originated primarily from within the country.
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Examining high magnitude grass pollen episodes at Worcester, United Kingdom, using back-Trajectory Analysis
Aerobiologia, 2005Co-Authors: Matt Smith, Jean Emberlin, Andrew KressAbstract:Trajectory Analysis is a valuable tool that has been used before in aerobiological studies, to investigate the movement of airborne pollen. This study has employed back-trajectories to examine the four highest grass pollen episodes at Worcester, during the 2001 grass pollen season. The results have shown that the highest grass pollen counts of the 2001 season were reached when air masses arrived from a westerly direction. Back-Trajectory Analysis has a limited value to forecasters because the method is retrospective and cannot be employed directly for forecasting. However, when used in conjunction with meteorological data this technique can be used to examine high magnitude events in order to identify conditions that lead to high pollen counts.
José García-rodríguez - One of the best experts on this subject based on the ideXlab platform.
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Human behaviour recognition based on Trajectory Analysis using neural networks
The 2013 International Joint Conference on Neural Networks (IJCNN), 2013Co-Authors: Jorge Azorín-lópez, Marcelo Saval-calvo, Andrés Fuster-guilló, José García-rodríguezAbstract:Automated human behaviour Analysis has been, and still remains, a challenging problem. It has been dealt from different points of views: from primitive actions to human interaction recognition. This paper is focused on Trajectory Analysis which allows a simple high level understanding of complex human behaviour. It is proposed a novel representation method of Trajectory data, called Activity Description Vector (ADV) based on the number of occurrences of a person is in a specific point of the scenario and the local movements that perform in it. The ADV is calculated for each cell of the scenario in which it is spatially sampled obtaining a cue for different clustering methods. The ADV representation has been tested as the input of several classic classifiers and compared to other approaches using CAVIAR dataset sequences obtaining great accuracy in the recognition of the behaviour of people in a Shopping Centre.
Alicja Stach - One of the best experts on this subject based on the ideXlab platform.
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examining ambrosia pollen episodes at poznan poland using back Trajectory Analysis
International Journal of Biometeorology, 2007Co-Authors: Alicja Stach, Matt Smith, Carsten Ambelas Skjoth, Jorgen BrandtAbstract:The pollen grains of Ambrosia spp. are considered to be important aeroallergens in parts of southern and central Europe. Back-trajectories have been analysed with the aim of finding the likely sources of Ambrosia pollen grains that arrived at Poznan (Poland). Temporal variations in Ambrosia pollen at Poznan from 1995–2005 were examined in order to identify Ambrosia pollen episodes suitable for further investigation using back-Trajectory Analysis. The trajectories were calculated using the transport model within the Lagrangian air pollution model, ACDEP (Atmospheric Chemistry and Deposition). Analysis identified two separate populations in Ambrosia pollen episodes, those that peaked in the early morning between 4 a.m. and 8 a.m., and those that peaked in the afternoon between 2 p.m. and 6 p.m.. Six Ambrosia pollen episodes between 2001 and 2005 were examined using back-Trajectory Analysis. The results showed that Ambrosia pollen episodes that peaked in the early morning usually arrived at Poznan from a southerly direction after passing over southern Poland, the Czech Republic, Slovakia and Hungary, whereas air masses that brought Ambrosia pollen to Poznan during the afternoon arrived from a more easterly direction and predominantly stayed within the borders of Poland. Back-Trajectory Analysis has shown that there is a possibility that long-range transport brings Ambrosia pollen to Poznan from southern Poland, the Czech Republic, Slovakia and Hungary. There is also a likelihood that Ambrosia is present in Poland, as shown by the arrival of pollen during the afternoon that originated primarily from within the country.
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Examining Ambrosia pollen episodes at Poznań (Poland) using back-Trajectory Analysis
International Journal of Biometeorology, 2006Co-Authors: Alicja Stach, Matt Smith, Carsten Ambelas Skjoth, Jorgen BrandtAbstract:The pollen grains of Ambrosia spp. are considered to be important aeroallergens in parts of southern and central Europe. Back-trajectories have been analysed with the aim of finding the likely sources of Ambrosia pollen grains that arrived at Poznan (Poland). Temporal variations in Ambrosia pollen at Poznan from 1995–2005 were examined in order to identify Ambrosia pollen episodes suitable for further investigation using back-Trajectory Analysis. The trajectories were calculated using the transport model within the Lagrangian air pollution model, ACDEP (Atmospheric Chemistry and Deposition). Analysis identified two separate populations in Ambrosia pollen episodes, those that peaked in the early morning between 4 a.m. and 8 a.m., and those that peaked in the afternoon between 2 p.m. and 6 p.m.. Six Ambrosia pollen episodes between 2001 and 2005 were examined using back-Trajectory Analysis. The results showed that Ambrosia pollen episodes that peaked in the early morning usually arrived at Poznan from a southerly direction after passing over southern Poland, the Czech Republic, Slovakia and Hungary, whereas air masses that brought Ambrosia pollen to Poznan during the afternoon arrived from a more easterly direction and predominantly stayed within the borders of Poland. Back-Trajectory Analysis has shown that there is a possibility that long-range transport brings Ambrosia pollen to Poznan from southern Poland, the Czech Republic, Slovakia and Hungary. There is also a likelihood that Ambrosia is present in Poland, as shown by the arrival of pollen during the afternoon that originated primarily from within the country.