Proceedings of the 9th International Conference on Distributed Smart Cameras最新文献

Robust and reliable step counting by mobile phone cameras 稳健可靠的步数计数的手机摄像头

Proceedings of the 9th International Conference on Distributed Smart Cameras Pub Date : 2015-09-08 DOI: 10.1145/2789116.2789120

Koray Ozcan, Senem Velipasalar

{"title":"Robust and reliable step counting by mobile phone cameras","authors":"Koray Ozcan, Senem Velipasalar","doi":"10.1145/2789116.2789120","DOIUrl":"https://doi.org/10.1145/2789116.2789120","url":null,"abstract":"Wearable sensors are being widely used to monitor daily human activities and vital signs. Accelerometer-based step counters are commonly available, especially after being integrated into smartphones and smart watches. Moreover, accelerometer data is also used to measure step length and frequency for indoor positioning systems. Yet, accelerometer-based algorithms are prone to over-counting, since they also count other routine movements, including movements of the phone, as steps. In addition, when users walk really slowly, or when they stop and start walking again, the accelerometer-based counting becomes unreliable. Since accurate step detection is very important for indoor positioning systems, more precise alternatives are needed for step detection and counting. In this paper, we present a robust and reliable method for counting foot steps using videos captured with a Samsung Galaxy® S4 smartphone. The performance of the proposed method is compared with existing accelerometer-based step counters. Experiments have been performed with different subjects carrying five mobile devices simultaneously, including smart phones and watches, at different locations on their body. The results show that camera-based step counting has the lowest average error rate for different users, and is more reliable compared to accelerometer-based counters. In addition, the results show the high sensitivity of the accelerometer-based step counters to the location of the device and high variance in their performance across different users.","PeriodicalId":113163,"journal":{"name":"Proceedings of the 9th International Conference on Distributed Smart Cameras","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130335113","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}

引用次数: 19

Compute-efficient eye state detection: algorithm, dataset and evaluations 计算效率高的眼状态检测:算法、数据集和评估

Proceedings of the 9th International Conference on Distributed Smart Cameras Pub Date : 2015-09-08 DOI: 10.1145/2789116.2789144

Supriya Sathyanarayana, R. Satzoda, T. Srikanthan, S. Sathyanarayana

引用次数: 2

Cooperative features extraction in visual sensor networks: a game-theoretic approach 视觉传感器网络中的协同特征提取:一种博弈论方法

Proceedings of the 9th International Conference on Distributed Smart Cameras Pub Date : 2015-09-08 DOI: 10.1145/2789116.2789124

A. Redondi, L. Baroffio, M. Cesana, M. Tagliasacchi

引用次数: 2

Mask and maskless face classification system to detect breach protocols in the operating room 面具和无面具面部分类系统，用于检测手术室的破坏协议

Proceedings of the 9th International Conference on Distributed Smart Cameras Pub Date : 2015-09-08 DOI: 10.1145/2789116.2802655

Adrian Nieto-Rodríguez, M. Mucientes, V. Brea

引用次数: 10

Detection of visitors in elderly care using a low-resolution visual sensor network 利用低分辨率视觉传感器网络检测老年人护理中的来访者

Proceedings of the 9th International Conference on Distributed Smart Cameras Pub Date : 2015-09-08 DOI: 10.1145/2789116.2789137

Mohamed Y. Eldib, Francis Deboeverie, D. V. Haerenborgh, W. Philips, H. Aghajan

{"title":"Detection of visitors in elderly care using a low-resolution visual sensor network","authors":"Mohamed Y. Eldib, Francis Deboeverie, D. V. Haerenborgh, W. Philips, H. Aghajan","doi":"10.1145/2789116.2789137","DOIUrl":"https://doi.org/10.1145/2789116.2789137","url":null,"abstract":"Loneliness is a common condition associated with aging and comes with extreme health consequences including decline in physical and mental health, increased mortality and poor living conditions. Detecting and assisting lonely persons is therefore important-especially in the home environment. The current studies analyse the Activities of Daily Living (ADL) usually with the focus on persons living alone, e.g., to detect health deterioration. However, this type of data analysis relies on the assumption of a single person being analysed, and the ADL data analysis becomes less reliable without assessing socialization in seniors for health state assessment and intervention. In this paper, we propose a network of cheap low-resolution visual sensors for the detection of visitors. The visitor analysis starts by visual feature extraction based on foreground/background detection and morphological operations to track the motion patterns in each visual sensor. Then, we utilize the features of the visual sensors to build a Hidden Markov Model (HMM) for the actual detection. Finally, a rule-based classifier is used to compute the number and the duration of visits. We evaluate our framework on a real-life dataset of ten months. The results show a promising visit detection performance when compared to ground truth.","PeriodicalId":113163,"journal":{"name":"Proceedings of the 9th International Conference on Distributed Smart Cameras","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115654050","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}

引用次数: 13

Low complexity FPGA based background subtraction technique for thermal imagery 基于FPGA的低复杂度热图像背景减去技术

Proceedings of the 9th International Conference on Distributed Smart Cameras Pub Date : 2015-09-08 DOI: 10.1145/2789116.2789121

Muhammad Imran, M. O’nils, H. Munir, Benny Thörnberg

{"title":"Low complexity FPGA based background subtraction technique for thermal imagery","authors":"Muhammad Imran, M. O’nils, H. Munir, Benny Thörnberg","doi":"10.1145/2789116.2789121","DOIUrl":"https://doi.org/10.1145/2789116.2789121","url":null,"abstract":"Embedded smart camera systems are gaining popularity for a number of real world surveillance applications. However, there are still challenges, i.e. variation in illumination, shadows, occlusion, and weather conditions while employing the vision algorithms in outdoor environments. For safety-critical surveillance applications, the visual sensors can be complemented with beyond-visual-range sensors. This in turn requires analysis, development and modification of existing imaging techniques. In this work, a low complexity background modelling and subtraction technique has been proposed for thermal imagery. The proposed technique has been implemented on Field Programmable Gate Arrays (FPGAs) after in-depth analysis of different sets of images, characterizing poor signal-to-noise ratio challenges, e.g. motion of high frequency background objects, temperature variation and camera jitter etc. The proposed technique dynamically updates the background on pixel level and requires a single frame storage as opposed to existing techniques. The comparison of this approach with two other approaches show that this approach performs better in different environmental conditions. The proposed technique has been modelled in Register Transfer Logic (RTL) and implementation on the latest FPGAs shows that the design requires less than 1 percent logics, 47 percent block RAMs, and consumes 91 mW power consumption on Artix-7 100T FPGA.","PeriodicalId":113163,"journal":{"name":"Proceedings of the 9th International Conference on Distributed Smart Cameras","volume":"127 40","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113939992","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}

引用次数: 1

Open-source and flexible framework for visual sensor networks 开放源代码和灵活的视觉传感器网络框架

Proceedings of the 9th International Conference on Distributed Smart Cameras Pub Date : 2015-09-08 DOI: 10.1145/2789116.2802650

L. Bondi, L. Baroffio, M. Cesana, A. Redondi, M. Tagliasacchi

引用次数: 6

The advantages and limitations of high level synthesis for FPGA based image processing 基于FPGA的图像处理高级合成的优点和局限性

Proceedings of the 9th International Conference on Distributed Smart Cameras Pub Date : 2015-09-08 DOI: 10.1145/2789116.2789145

D. Bailey

引用次数: 29

Real-time multi-people tracking by greedy likelihood maximization 基于贪婪似然最大化的实时多人跟踪

Proceedings of the 9th International Conference on Distributed Smart Cameras Pub Date : 2015-09-08 DOI: 10.1145/2789116.2789125

Nyan Bo Bo, Francis Deboeverie, P. Veelaert, W. Philips

{"title":"Real-time multi-people tracking by greedy likelihood maximization","authors":"Nyan Bo Bo, Francis Deboeverie, P. Veelaert, W. Philips","doi":"10.1145/2789116.2789125","DOIUrl":"https://doi.org/10.1145/2789116.2789125","url":null,"abstract":"Unlike tracking rigid targets, the task of tracking multiple people is very challenging because the appearance and the shape of a person varies depending on the target's location and orientation. This paper presents a new approach to track multiple people with high accuracy using a calibrated monocular camera. Our approach recursively updates the positions of all persons based on the observed foreground image and previously known location of each person. This is done by maximizing the likelihood of observing the foreground image given the positions of all persons. Since the computational complexity of our approach is low, it is possible to run in real time on smart cameras. When a network of multiple smart cameras overseeing the scene is available, local position estimates from smart cameras can be fused to produced more accurate joint position estimates. The performance evaluation of our approach on very challenging video sequences from public datasets shows that our tracker achieves high accuracy. When comparing to other state-of-the-art tracking systems, our method outperforms in terms of Multiple Object Tracking Accuracy (MOTA).","PeriodicalId":113163,"journal":{"name":"Proceedings of the 9th International Conference on Distributed Smart Cameras","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134545877","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}

引用次数: 6

Using dominant sets for data association in multi-camera tracking 基于优势集的多相机跟踪数据关联

Proceedings of the 9th International Conference on Distributed Smart Cameras Pub Date : 2015-09-08 DOI: 10.1145/2789116.2789126

A. Hamid, Surafel Melaku Lakew, M. Pelillo, A. Prati

引用次数: 1