The number of elderly population is increasing worldwide and often they need assistance in their daily activities. In many situations, these elders are placed in elderly care facilities in order to receive continuous assistance from the human caregivers. The caregivers usually keep a watchful eye on the elders and help them in their activities of daily living. However, study shows that the human caregivers often suffer from boredom for being engaged in monitoring the elderly, which also compromises the care and assistance needed for the vulnerable elderly. In order to address this issue, we propose a human caregiver support system that aims to comprehend elderly persons' activities and decides what services to provide them in different situations and when to notify the human caregiver about any incident that happens in the care facility. Our preliminary experiment shows the potential of such system.
{"title":"A Human Caregiver Support System in Elderly Monitoring Facility","authors":"M. A. Hossain, D. Ahmed","doi":"10.1109/ICMEW.2012.82","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.82","url":null,"abstract":"The number of elderly population is increasing worldwide and often they need assistance in their daily activities. In many situations, these elders are placed in elderly care facilities in order to receive continuous assistance from the human caregivers. The caregivers usually keep a watchful eye on the elders and help them in their activities of daily living. However, study shows that the human caregivers often suffer from boredom for being engaged in monitoring the elderly, which also compromises the care and assistance needed for the vulnerable elderly. In order to address this issue, we propose a human caregiver support system that aims to comprehend elderly persons' activities and decides what services to provide them in different situations and when to notify the human caregiver about any incident that happens in the care facility. Our preliminary experiment shows the potential of such system.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126956562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We present a novel method for computing depth of field and geometry from a single 2D image. This technique, unlike the existing ones measures the absolute depth of field and distances in the scene from single image only using the concept of triangulation. This algorithm requires minimum inputs such as camera height, camera pitch angle and camera field of view for computing the depth of field and 3D coordinates of any given point in the image. In addition, this method can be used to compute the actual size of an object in the scene (width and height) as well as the distance between different objects in the image. The proposed methodology has the potential to be implemented in high impact applications such as distance measurement from mobile phones, robot navigation and aerial surveillances.
{"title":"Depth and Geometry from a Single 2D Image Using Triangulation","authors":"Yasir Salih, A. Malik","doi":"10.1109/ICMEW.2012.95","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.95","url":null,"abstract":"We present a novel method for computing depth of field and geometry from a single 2D image. This technique, unlike the existing ones measures the absolute depth of field and distances in the scene from single image only using the concept of triangulation. This algorithm requires minimum inputs such as camera height, camera pitch angle and camera field of view for computing the depth of field and 3D coordinates of any given point in the image. In addition, this method can be used to compute the actual size of an object in the scene (width and height) as well as the distance between different objects in the image. The proposed methodology has the potential to be implemented in high impact applications such as distance measurement from mobile phones, robot navigation and aerial surveillances.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122001685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The benefits of passing partially corrupted packets to the application instead of discarding them have been debated actively, since Lightweight User Data gram Protocol (UDP Lite) was introduced. UDP Lite allows partial check summing in order to omit bit errors in the non-critical part of the packet payload. Several studies have shown that data throughput over a link prone to bit errors can be significantly improved with partial check summing. However, the higher throughput comes at the cost of bit errors appearing in the non-critical parts of the payload. Therefore, the overall benefit depends highly on the capability of coping with errors at the application layer. In this paper, we present a theoretical framework for defining the optimal level of partial checksum protection, assuming that the bit error characteristics and the perceptual impact of bit errors appearing in the non-protected parts of the payload are known. We have also derived experimentally the distortion levels for video sequences coded with different bit rates and protection levels in the presence of bit errors. The results show that in some scenarios it is possible to improve the perceived overall video quality by using partial check summing.
{"title":"Theoretical Framework for Evaluating Partial Checksum Protection in Wireless Video Streaming","authors":"J. Korhonen, Søren Forchhammer, K. J. Larsen","doi":"10.1109/ICMEW.2012.118","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.118","url":null,"abstract":"The benefits of passing partially corrupted packets to the application instead of discarding them have been debated actively, since Lightweight User Data gram Protocol (UDP Lite) was introduced. UDP Lite allows partial check summing in order to omit bit errors in the non-critical part of the packet payload. Several studies have shown that data throughput over a link prone to bit errors can be significantly improved with partial check summing. However, the higher throughput comes at the cost of bit errors appearing in the non-critical parts of the payload. Therefore, the overall benefit depends highly on the capability of coping with errors at the application layer. In this paper, we present a theoretical framework for defining the optimal level of partial checksum protection, assuming that the bit error characteristics and the perceptual impact of bit errors appearing in the non-protected parts of the payload are known. We have also derived experimentally the distortion levels for video sequences coded with different bit rates and protection levels in the presence of bit errors. The results show that in some scenarios it is possible to improve the perceived overall video quality by using partial check summing.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124687321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
OpenGL SC, the safety critical profile of OpenGL plays the major role for the graphical user interfaces, especially in the safety-critical markets, including avionics, military, medical and automotive applications. In other side, OpenGL ES, the embedded systems version of OpenGL, has many commercial implementations. In this demonstration, we show that the OpenGL SC features can be provided over the wide-spread OpenGL ES graphics boards. This is the most cost-effective way of implementing OpenGL SC, at this time. Our result is the first implementation based on OpenGL ES 1.1 hardware. We will demonstrate this OpenGL SC-over-OpenGL ES 1.1 implementation, and show its successful behaviors.
OpenGL SC, OpenGL的安全关键配置文件在图形用户界面中起着主要作用，特别是在安全关键市场，包括航空电子，军事，医疗和汽车应用。另一方面，OpenGL的嵌入式系统版本OpenGL ES有许多商业实现。在这个演示中，我们展示了OpenGL SC特性可以在广泛的OpenGL ES图形板上提供。这是目前实现OpenGL SC最具成本效益的方法。我们的结果是基于OpenGL ES 1.1硬件的第一个实现。我们将演示这个OpenGL SC-over-OpenGL ES 1.1实现，并展示其成功的行为。
{"title":"OpenGL SC Implementation over an OpenGL ES 1.1 Graphics Board","authors":"Nakhoon Baek, Hwanyong Lee","doi":"10.1109/ICMEW.2012.127","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.127","url":null,"abstract":"OpenGL SC, the safety critical profile of OpenGL plays the major role for the graphical user interfaces, especially in the safety-critical markets, including avionics, military, medical and automotive applications. In other side, OpenGL ES, the embedded systems version of OpenGL, has many commercial implementations. In this demonstration, we show that the OpenGL SC features can be provided over the wide-spread OpenGL ES graphics boards. This is the most cost-effective way of implementing OpenGL SC, at this time. Our result is the first implementation based on OpenGL ES 1.1 hardware. We will demonstrate this OpenGL SC-over-OpenGL ES 1.1 implementation, and show its successful behaviors.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124859977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Crowd density estimation is important for intelligent video surveillance. Many methods based on texture features have been proposed to solve this problem. Most of the existing algorithms only estimate crowd density on the whole image while ignore crowd density in local region. In this paper, we propose a novel texture descriptor based on Local Binary Pattern (LBP) Co-occurrence Matrix (LBPCM) for crowd density estimation. LBPCM is constructed from several overlapping cells in an image block, which is going to be classified into different crowd density levels. LBPCM describes both the statistical properties and the spatial information of LBP and thus makes full use of LBP for local texture features. Additionally, we both extract LBPCM on gray and gradient images to improve the performance of crowd density estimation. Finally, the sliding window technique is used to detect the potential crowded area. The experimental results show the proposed method has better performance than other texture based crowd density estimation methods.
{"title":"Crowd Density Estimation Based on Local Binary Pattern Co-Occurrence Matrix","authors":"Zhe Wang, Hong Liu, Yueliang Qian, Tao Xu","doi":"10.1109/ICMEW.2012.71","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.71","url":null,"abstract":"Crowd density estimation is important for intelligent video surveillance. Many methods based on texture features have been proposed to solve this problem. Most of the existing algorithms only estimate crowd density on the whole image while ignore crowd density in local region. In this paper, we propose a novel texture descriptor based on Local Binary Pattern (LBP) Co-occurrence Matrix (LBPCM) for crowd density estimation. LBPCM is constructed from several overlapping cells in an image block, which is going to be classified into different crowd density levels. LBPCM describes both the statistical properties and the spatial information of LBP and thus makes full use of LBP for local texture features. Additionally, we both extract LBPCM on gray and gradient images to improve the performance of crowd density estimation. Finally, the sliding window technique is used to detect the potential crowded area. The experimental results show the proposed method has better performance than other texture based crowd density estimation methods.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129972319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recently, a content-preserving warping algorithm utilizing 3D motion has been acknowledged as state-of-the-art thanks to its superior stabilization performance. However, the huge computational cost of this technique is a serious burden in spite of its excellent performance. Thus, we propose a fast video stabilization algorithm that provides significantly reduced computational complexity over the state-of-the-art with the same stabilization performance. First, we estimate the 3D information of the feature points in each input frame and define the region of interest (ROI) based on the estimated 3D information. Next, we apply the proposed ROI-based pre-warping and content-preserving warping sequentially to the input frame. From intensive simulation results, we find that the proposed algorithm reduces computational complexity by 15% of that of the state-of-the-art method, while keeping almost equivalent stabilization performance.
{"title":"ROI-Based Video Stabilization Algorithm for Hand-Held Cameras","authors":"Dong-Bok Lee, Ick-hyun Choi, B. Song, T. Lee","doi":"10.1109/ICMEW.2012.60","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.60","url":null,"abstract":"Recently, a content-preserving warping algorithm utilizing 3D motion has been acknowledged as state-of-the-art thanks to its superior stabilization performance. However, the huge computational cost of this technique is a serious burden in spite of its excellent performance. Thus, we propose a fast video stabilization algorithm that provides significantly reduced computational complexity over the state-of-the-art with the same stabilization performance. First, we estimate the 3D information of the feature points in each input frame and define the region of interest (ROI) based on the estimated 3D information. Next, we apply the proposed ROI-based pre-warping and content-preserving warping sequentially to the input frame. From intensive simulation results, we find that the proposed algorithm reduces computational complexity by 15% of that of the state-of-the-art method, while keeping almost equivalent stabilization performance.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130011831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Omidyeganeh, A. Javadtalab, S. Ghaemmaghami, S. Shirmohammadi
A robust fingerprint recognition system based on marginal statistics of 2D wavelet transform is introduced which significantly improves the accuracy of previous wavelet based approaches due to 1) a better selection of features extracted from the wavelet transform, and 2) a more accurate distance measure to find the similarity between fingerprints. A combination of Jain and Poincare algorithms is employed to locate the fingerprint reference point. The main part of the fingerprint image is chosen as a rectangle with the reference point at its center. The image is then divided into nonoverlapping sub-images, the wavelet transform is applied to the bi-level sub-images, and Generalized Gaussian Density (GGD) features are extracted from each wavelet sub band. Finally, the fingerprint recognition is done through the k-Nearest Neighbor (k-NN) classification employing Kullback-Leibler Distance (KLD) measure. Our test results confirm the superiority of the proposed method over the current fingerprint recognition methods.
{"title":"A Robust Wavelet-based Approach to Fingerprint Indentification","authors":"M. Omidyeganeh, A. Javadtalab, S. Ghaemmaghami, S. Shirmohammadi","doi":"10.1109/ICMEW.2012.78","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.78","url":null,"abstract":"A robust fingerprint recognition system based on marginal statistics of 2D wavelet transform is introduced which significantly improves the accuracy of previous wavelet based approaches due to 1) a better selection of features extracted from the wavelet transform, and 2) a more accurate distance measure to find the similarity between fingerprints. A combination of Jain and Poincare algorithms is employed to locate the fingerprint reference point. The main part of the fingerprint image is chosen as a rectangle with the reference point at its center. The image is then divided into nonoverlapping sub-images, the wavelet transform is applied to the bi-level sub-images, and Generalized Gaussian Density (GGD) features are extracted from each wavelet sub band. Finally, the fingerprint recognition is done through the k-Nearest Neighbor (k-NN) classification employing Kullback-Leibler Distance (KLD) measure. Our test results confirm the superiority of the proposed method over the current fingerprint recognition methods.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124430704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we propose a new background subtraction technique based on perceptual mixture-of-Gaussians (PMOG). Unlike numerous variants of the classical MOG based approach [1], which can ensure reliable detection result only in known operating environments through proper parameter tuning, PMOG shows superior detection performance across dynamic unconstrained scenarios without any tuning. This is due to PMOG's intrinsic capability of exploiting several perceptual characteristics of human visual system for better understanding of the operating environment to avoid blind reliance on statistical observations. Furthermore, the proposed technique dynamically varies the model adaptation speed, i.e., learning rate, based on observed scene statistics for faster adaptation of changed background and better persistency of detected foreground entities. Comprehensive experimental evaluation on a number of standard datasets validates the robustness of the technique compared to the state-of-the-art.
{"title":"Robust Background Subtraction Based on Perceptual Mixture-of-Gaussians with Dynamic Adaptation Speed","authors":"Mahfuzul Haque, M. Murshed","doi":"10.1109/ICMEW.2012.75","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.75","url":null,"abstract":"In this paper, we propose a new background subtraction technique based on perceptual mixture-of-Gaussians (PMOG). Unlike numerous variants of the classical MOG based approach [1], which can ensure reliable detection result only in known operating environments through proper parameter tuning, PMOG shows superior detection performance across dynamic unconstrained scenarios without any tuning. This is due to PMOG's intrinsic capability of exploiting several perceptual characteristics of human visual system for better understanding of the operating environment to avoid blind reliance on statistical observations. Furthermore, the proposed technique dynamically varies the model adaptation speed, i.e., learning rate, based on observed scene statistics for faster adaptation of changed background and better persistency of detected foreground entities. Comprehensive experimental evaluation on a number of standard datasets validates the robustness of the technique compared to the state-of-the-art.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115585274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Almost every aspect of how we create, transmit, and consume video has changed, but video interfaces still mimic those from video's inception. We extend Temporal Semantic Compression for interactive video browsing, which uses an arbitrary frame-by-frame interest measure to sub-sample video in real time, with user interface elements that visualize these measures and the effect of compressing on them. We experiment with a novel interest measure for popularity, and design novel visualizations for expressing interest measures and the compression interaction. We conduct the first formative evaluation of the TSC paradigm, with 8 subjects, and report design implications arising from it.
{"title":"Towards a Video Browser for the Digital Native","authors":"Brett Adams, S. Greenhill, S. Venkatesh","doi":"10.1109/ICMEW.2012.29","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.29","url":null,"abstract":"Almost every aspect of how we create, transmit, and consume video has changed, but video interfaces still mimic those from video's inception. We extend Temporal Semantic Compression for interactive video browsing, which uses an arbitrary frame-by-frame interest measure to sub-sample video in real time, with user interface elements that visualize these measures and the effect of compressing on them. We experiment with a novel interest measure for popularity, and design novel visualizations for expressing interest measures and the compression interaction. We conduct the first formative evaluation of the TSC paradigm, with 8 subjects, and report design implications arising from it.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123337222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper develops a novel method to automatically categorize different animation genres in a video database made for children, this is the first such research done in animation genre categorization. The method is based on statistically modeling the temporal texture attributes of the video sequence. The features are extracted from gray-level co-occurrence matrices and a hidden Markov models (HMM) are used as a classifier. It was found the method had 16.66% better accuracy compared to other methods with the same number of parameters and dimensions of feature vector.
{"title":"A Textural Based Hidden Markov Model for Animation Genre Discrimination","authors":"Joseph Santarcangelo, Xiao-Ping Zhang","doi":"10.1109/ICMEW.2012.102","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.102","url":null,"abstract":"This paper develops a novel method to automatically categorize different animation genres in a video database made for children, this is the first such research done in animation genre categorization. The method is based on statistically modeling the temporal texture attributes of the video sequence. The features are extracted from gray-level co-occurrence matrices and a hidden Markov models (HMM) are used as a classifier. It was found the method had 16.66% better accuracy compared to other methods with the same number of parameters and dimensions of feature vector.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123979560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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