DaeHee Kim - Academia.edu (original) (raw)
Papers by DaeHee Kim
This paper presents a gait recognition algorithm for human identification from a sequence of segm... more This paper presents a gait recognition algorithm for human identification from a sequence of segmented noisy silhouettes in a low-resolution video. The main contribution of the proposed work is the use of the hierarchical recovery of a static body and stride parameters of model subjects to the walking pose. The proposed algorithm overcomes drawbacks of existing works by extracting a set of relative model parameters instead of directly analyzing the gait pattern. The feature extraction function in the proposed algorithm consists of motion detection, object region detection, and active shape model (ASM), which alleviate problem in the baseline algorithm such as; background generation, shadow removal, and higher recognition rate. Performance of the proposed algorithm has been evaluated by using the HumanID Gait Challenge data set, which is the largest gait benchmarking data set with 122 objects with different realistic parameters including viewpoint, shoe, surface, carrying condition, and time.
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Psycho-oncology, 2009
Objective: Parents of children with cancer must cope with multiple challenges over time. As most ... more Objective: Parents of children with cancer must cope with multiple challenges over time. As most research on parental coping has been conducted in Western countries, little information is available on the parental experience of coping in non-Western countries. Using a new cultural sample of Korean mothers, this study describes their coping strategies. In addition, the association of particular coping patterns with mothers' report of psychosocial adjustment is investigated.Methods: A total of 200 Korean mothers of children with cancer participated in the study. Coping strategies were measured by the Coping Health Inventory for Parents in the following three categories: Maintaining Family Integration and an Optimistic Outlook for the Situation, Seeking Social Support, and Seeking Information. Maternal psychosocial adjustment was measured by psychological distress, family relationship, and social relationship subscales from the Psychosocial Adjustment to Illness Scale.Results: Korean mothers reported coping strategies related to Maintaining Family Integration and an Optimistic Outlook for the Situation as being most helpful. More frequent use of coping pattern, Maintaining Family Integration and an Optimistic Outlook for the Situation, and less frequent use of coping pattern, Information-Seeking were significantly associated with lower psychological distress and better family relationship after children's medical and maternal characteristics were controlled for. Coping pattern, Seeking Social Support was only predictive of social relationships.Conclusions: This study suggests that culture may play a significant role in the report of coping among Korean mothers. Future studies should consider culturally preferred coping methods and available resources as they relate to different adjustment outcomes. Copyright © 2008 John Wiley & Sons, Ltd.
Bookmarks Related papers MentionsView impact
This paper presents a feature fusion-based tracking algorithm using optical flow under the non-pr... more This paper presents a feature fusion-based tracking algorithm using optical flow under the non-prior training active feature model (NPT-AFM) framework. The proposed object tracking procedure can be divided into three steps: (i) localization of human objects, (ii) prediction and correction of the object’s location by utilizing spatio-temporal information, and (iii) restoration of occlusion using the NPT-AFM[15]. Feature points inside an ellipsoidal shape including objects are estimated instead of its shape boundary, and are updated as an element of the training set for the AFM. Although the proposed algorithm uses the greatly reduced number of feature points, the proposed feature fusion-based multiple people tracking algorithm enables the tracking of occluded people in complicated background.
Bookmarks Related papers MentionsView impact
In block-based coding schemes, the input image is segmented into small blocks that are processed ... more In block-based coding schemes, the input image is segmented into small blocks that are processed independently; therefore, blocking effects occur along block boundaries. Various methods have been developed to reduce such blocking effects. In this paper, we propose a method for blocking effect reduction based on optimal filtering, and we compare its performance with those of others.
Bookmarks Related papers MentionsView impact
Tracking non-rigid objects such as people in video sequences is a daunting task due to computatio... more Tracking non-rigid objects such as people in video sequences is a daunting task due to computational complexity and unpredictable environment. The analysis and interpretation of video sequence containing moving, deformable objects have been an active research areas including video tracking, computer vision, and pattern recognition. In this paper we propose a robust, model-based, real-time system to cope with background clutter and occlusion. The proposed algorithm consists of following four steps: (i) localization of an object-of-interest by analyzing four directional motions, (ii) region tracker for tracking moving region detected by the motion detector, (iii) update of training sets using the Smart Snake Algorithm (SSA) without preprocessing, (iv) active shape model-based tracking in region information. The major contribution this work lies in the integration for a completed system, which covers from image processing to tracking algorithms. The approach of combining multiple algorithms succeeds in overcoming fundamental limitations of tracking and at the same time realizes real time implementation. Experimental results show that the proposed algorithm can track people under various environment in real-time. The proposed system has potential uses in the area of surveillance, sape analysis, and model-based coding, to name of few.
Bookmarks Related papers MentionsView impact
We present a gait recognition system using infra-red (IR) images. Since an IR camera is not affec... more We present a gait recognition system using infra-red (IR) images. Since an IR camera is not affected by the intensity of illumination, it is able to provide constant recognition performance regardless of the amount of illumination. Model-based object tracking algorithms enable robust tracking with partial occlusions or dynamic illumination. However, this algorithm often fails in tracking objects if strong edge exists near the object. Replacement of the input image by an IR image guarantees robust object region extraction because background edges do not affect the IR image. In conclusion, the proposed gait recognition algorithm improves accuracy in object extraction by using IR images and the improvements finally increase the recognition rate of gaits.
Bookmarks Related papers MentionsView impact
Active Shape Model (ASM) paradigm is a popular method for image segmentation where a priori infor... more Active Shape Model (ASM) paradigm is a popular method for image segmentation where a priori information about the shape of the object of interest is available. The effectiveness of the method is contingent upon a correct correspondence between model points and the features extracted from the image. Extensive application of these models soon revealed one of their limitations when, for a given model point, no obvious salient point can be found in the image. The primary cause of such limitation is due to weak edges and presence of abrupt noise which is the case with low light surveillance video images. In this paper we propose a fusion-based panoramic tracking algorithm of in low light images using multiple sensors. The proposed algorithm uses an IR and CCD sensor for image capture. The proposed tracking system consists of three steps: (i) pyramid based fusion algorithm, (ii) reconstruction of panoramic image, and (iii) active shape model (ASM)-based tracking algorithm. The experimental results show that the proposed tracking system can robustly extract and track objects on panoramic images in real-time.
Bookmarks Related papers MentionsView impact
This paper presents a gait recognition algorithm for human identification from a sequence of segm... more This paper presents a gait recognition algorithm for human identification from a sequence of segmented noisy silhouettes in a low-resolution video. The main contribution of the proposed work is the use of the hierarchical recovery of a static body and stride parameters of model subjects to the walking pose. The proposed algorithm overcomes drawbacks of existing works by extracting a set of relative model parameters instead of directly analyzing the gait pattern. The feature extraction function in the proposed algorithm consists of motion detection, object region detection, and active shape model (ASM), which alleviate problem in the baseline algorithm such as; background generation, shadow removal, and higher recognition rate. Performance of the proposed algorithm has been evaluated by using the HumanID Gait Challenge data set, which is the largest gait benchmarking data set with 122 objects with different realistic parameters including viewpoint, shoe, surface, carrying condition, and time.
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Psycho-oncology, 2009
Objective: Parents of children with cancer must cope with multiple challenges over time. As most ... more Objective: Parents of children with cancer must cope with multiple challenges over time. As most research on parental coping has been conducted in Western countries, little information is available on the parental experience of coping in non-Western countries. Using a new cultural sample of Korean mothers, this study describes their coping strategies. In addition, the association of particular coping patterns with mothers' report of psychosocial adjustment is investigated.Methods: A total of 200 Korean mothers of children with cancer participated in the study. Coping strategies were measured by the Coping Health Inventory for Parents in the following three categories: Maintaining Family Integration and an Optimistic Outlook for the Situation, Seeking Social Support, and Seeking Information. Maternal psychosocial adjustment was measured by psychological distress, family relationship, and social relationship subscales from the Psychosocial Adjustment to Illness Scale.Results: Korean mothers reported coping strategies related to Maintaining Family Integration and an Optimistic Outlook for the Situation as being most helpful. More frequent use of coping pattern, Maintaining Family Integration and an Optimistic Outlook for the Situation, and less frequent use of coping pattern, Information-Seeking were significantly associated with lower psychological distress and better family relationship after children's medical and maternal characteristics were controlled for. Coping pattern, Seeking Social Support was only predictive of social relationships.Conclusions: This study suggests that culture may play a significant role in the report of coping among Korean mothers. Future studies should consider culturally preferred coping methods and available resources as they relate to different adjustment outcomes. Copyright © 2008 John Wiley & Sons, Ltd.
Bookmarks Related papers MentionsView impact
This paper presents a feature fusion-based tracking algorithm using optical flow under the non-pr... more This paper presents a feature fusion-based tracking algorithm using optical flow under the non-prior training active feature model (NPT-AFM) framework. The proposed object tracking procedure can be divided into three steps: (i) localization of human objects, (ii) prediction and correction of the object’s location by utilizing spatio-temporal information, and (iii) restoration of occlusion using the NPT-AFM[15]. Feature points inside an ellipsoidal shape including objects are estimated instead of its shape boundary, and are updated as an element of the training set for the AFM. Although the proposed algorithm uses the greatly reduced number of feature points, the proposed feature fusion-based multiple people tracking algorithm enables the tracking of occluded people in complicated background.
Bookmarks Related papers MentionsView impact
In block-based coding schemes, the input image is segmented into small blocks that are processed ... more In block-based coding schemes, the input image is segmented into small blocks that are processed independently; therefore, blocking effects occur along block boundaries. Various methods have been developed to reduce such blocking effects. In this paper, we propose a method for blocking effect reduction based on optimal filtering, and we compare its performance with those of others.
Bookmarks Related papers MentionsView impact
Tracking non-rigid objects such as people in video sequences is a daunting task due to computatio... more Tracking non-rigid objects such as people in video sequences is a daunting task due to computational complexity and unpredictable environment. The analysis and interpretation of video sequence containing moving, deformable objects have been an active research areas including video tracking, computer vision, and pattern recognition. In this paper we propose a robust, model-based, real-time system to cope with background clutter and occlusion. The proposed algorithm consists of following four steps: (i) localization of an object-of-interest by analyzing four directional motions, (ii) region tracker for tracking moving region detected by the motion detector, (iii) update of training sets using the Smart Snake Algorithm (SSA) without preprocessing, (iv) active shape model-based tracking in region information. The major contribution this work lies in the integration for a completed system, which covers from image processing to tracking algorithms. The approach of combining multiple algorithms succeeds in overcoming fundamental limitations of tracking and at the same time realizes real time implementation. Experimental results show that the proposed algorithm can track people under various environment in real-time. The proposed system has potential uses in the area of surveillance, sape analysis, and model-based coding, to name of few.
Bookmarks Related papers MentionsView impact
We present a gait recognition system using infra-red (IR) images. Since an IR camera is not affec... more We present a gait recognition system using infra-red (IR) images. Since an IR camera is not affected by the intensity of illumination, it is able to provide constant recognition performance regardless of the amount of illumination. Model-based object tracking algorithms enable robust tracking with partial occlusions or dynamic illumination. However, this algorithm often fails in tracking objects if strong edge exists near the object. Replacement of the input image by an IR image guarantees robust object region extraction because background edges do not affect the IR image. In conclusion, the proposed gait recognition algorithm improves accuracy in object extraction by using IR images and the improvements finally increase the recognition rate of gaits.
Bookmarks Related papers MentionsView impact
Active Shape Model (ASM) paradigm is a popular method for image segmentation where a priori infor... more Active Shape Model (ASM) paradigm is a popular method for image segmentation where a priori information about the shape of the object of interest is available. The effectiveness of the method is contingent upon a correct correspondence between model points and the features extracted from the image. Extensive application of these models soon revealed one of their limitations when, for a given model point, no obvious salient point can be found in the image. The primary cause of such limitation is due to weak edges and presence of abrupt noise which is the case with low light surveillance video images. In this paper we propose a fusion-based panoramic tracking algorithm of in low light images using multiple sensors. The proposed algorithm uses an IR and CCD sensor for image capture. The proposed tracking system consists of three steps: (i) pyramid based fusion algorithm, (ii) reconstruction of panoramic image, and (iii) active shape model (ASM)-based tracking algorithm. The experimental results show that the proposed tracking system can robustly extract and track objects on panoramic images in real-time.
Bookmarks Related papers MentionsView impact