2020 15th IEEE International Conference on Signal Processing (ICSP)最新文献

Driving and localization design of a multi-sensor transport robot 多传感器运输机器人的驱动与定位设计

2020 15th IEEE International Conference on Signal Processing (ICSP) Pub Date : 2020-12-06 DOI: 10.1109/ICSP48669.2020.9320913

Hongxia Wang, Shengfeng Xu, Yuzheng Zhang, Qicheng Liu, Ji Deng, Yicheng Mou, Chengkun Shi

引用次数: 0

Appearance-Based Gaze Tracking Through Supervised Machine Learning 通过监督机器学习的基于外观的凝视跟踪

2020 15th IEEE International Conference on Signal Processing (ICSP) Pub Date : 2020-12-06 DOI: 10.1109/ICSP48669.2020.9321075

Daniel Melesse, Mahmoud Khalil, Elias Kagabo, T. Ning, Kevin Huang

{"title":"Appearance-Based Gaze Tracking Through Supervised Machine Learning","authors":"Daniel Melesse, Mahmoud Khalil, Elias Kagabo, T. Ning, Kevin Huang","doi":"10.1109/ICSP48669.2020.9321075","DOIUrl":"https://doi.org/10.1109/ICSP48669.2020.9321075","url":null,"abstract":"Applications that use human gaze have become increasingly more popular in the domain of human-computer interfaces, and advances in eye gaze tracking technology over the past few decades have led to the development of promising gaze estimation techniques. In this paper, a low-cost, in-house video camera-based gaze tracking system was developed, trained and evaluated. Seminal gaze detection methods constrained the application space to indoor conditions, and in most cases techniques required intrusive hardware. More modern gaze detection techniques try to eliminate the use of any additional hardware to reduce monetary cost as well as undue burden to the user, all the while maintaining accuracy of detection. In this work, image acquisition was achieved using a low-cost USB web camera mounted at a fixed position on the viewing screen or laptop. In order to determine the point of gaze, the Viola Jones face detection algorithm is used to extract facial features from the image frame. The gaze is then calculated using image processing techniques to extract gaze features, namely related to the image position of the pupil. Thousands of images are classified and labeled to form an in-house database. A multi-class Support Vector Machine (SVM) was trained and tested on this data set to distinguish point of gaze from input face image. Cross validation was used to train the model. Confusion matrices, accuracy, precision, and recall are used to evaluate the performance of the classification model. Evaluation of the proposed appearance-based technique using two different kernel functions is also assessed in detail.","PeriodicalId":237073,"journal":{"name":"2020 15th IEEE International Conference on Signal Processing (ICSP)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121028675","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

Localization of Closely-Spaced Speech Sources Based on Small Microphone Arrays 基于小麦克风阵列的近间隔语音源定位

2020 15th IEEE International Conference on Signal Processing (ICSP) Pub Date : 2020-12-06 DOI: 10.1109/ICSP48669.2020.9320993

Siyu Sun, Qinmengying Yan, Wusheng Zhang, Haijian Zhang

{"title":"Localization of Closely-Spaced Speech Sources Based on Small Microphone Arrays","authors":"Siyu Sun, Qinmengying Yan, Wusheng Zhang, Haijian Zhang","doi":"10.1109/ICSP48669.2020.9320993","DOIUrl":"https://doi.org/10.1109/ICSP48669.2020.9320993","url":null,"abstract":"Indoor source localization based on a microphone array is still a difficult problem especially for closely-spaced sources in strong reverberation environments, in such cases a large number of microphones are often utilized. Considering the industrial design and cost, source localization using a small microphone array in complex conditions is worthy of investigation. In this paper, we propose a small-size array based localization method under the condition of close proximity and strong reverberation. The essence of the proposed method lies in the detection of single source time-frequency (TF) points (SSPs) of each source, which simplifies the problem of multisource localization in close proximity into several single-source localization ones. The detected SSPs are then used for precise source localization in a sparse Bayesian framework, wherein the reflection coefficient can be simultaneously estimated by implementing a Bayesian dictionary learning. Experimental results confirm the effectiveness of our method in locating spatially-close sources compared with some state-of-the-art methods.","PeriodicalId":237073,"journal":{"name":"2020 15th IEEE International Conference on Signal Processing (ICSP)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123714617","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: 0

An Efficient Lightweight Object Detector for Railway Tunnel Safety Monitoring 一种用于铁路隧道安全监测的轻型目标探测器

2020 15th IEEE International Conference on Signal Processing (ICSP) Pub Date : 2020-12-06 DOI: 10.1109/ICSP48669.2020.9320914

Enze Yang, Yuxin Liu, Shuoyan Liu

{"title":"An Efficient Lightweight Object Detector for Railway Tunnel Safety Monitoring","authors":"Enze Yang, Yuxin Liu, Shuoyan Liu","doi":"10.1109/ICSP48669.2020.9320914","DOIUrl":"https://doi.org/10.1109/ICSP48669.2020.9320914","url":null,"abstract":"Tunnel disaster usually poses a huge threat to trains and passengers, hence the monitoring of the tunnel environment becomes particularly important. In this paper, we aim to detect the potential tunnel disasters from the perspective of computer vision. An efficient lightweight network is proposed to mainly detect pedestrians and trains in tunnel, a lightweight backbone is leveraged to reduce the volume of network parameters and computational costs, while multi-scale feature fusion enhances the spatial and semantic features of various layers. As a foreground mask to the Gaussian Mixture Model, our detector aims to improve the performance of obstacle detection by reducing the false alarm rate. A number of experiments are carried out in the tunnel laboratory. According to experimental results, the detection framework proposed in this paper beats the state-of-the-art detectors in tunnel dataset. Further, the mask generated by the detector significantly decreases the false alarm rate of the Gaussian Mixture Model of obstacle detection, which proves that the framework proposed in this paper is applicable to practical tunnel safety monitoring.","PeriodicalId":237073,"journal":{"name":"2020 15th IEEE International Conference on Signal Processing (ICSP)","volume":"16 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122584037","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: 2

Bernoulli Track-before-detect Algorithm for Distributed Target with Unknown Amplitude Information 具有未知幅值信息的分布式目标的伯努利检测前跟踪算法

2020 15th IEEE International Conference on Signal Processing (ICSP) Pub Date : 2020-12-06 DOI: 10.1109/ICSP48669.2020.9321019

Ruofeng Yu, Wei Yang, Yaowen Fu, Wenpeng Zhang

{"title":"Bernoulli Track-before-detect Algorithm for Distributed Target with Unknown Amplitude Information","authors":"Ruofeng Yu, Wei Yang, Yaowen Fu, Wenpeng Zhang","doi":"10.1109/ICSP48669.2020.9321019","DOIUrl":"https://doi.org/10.1109/ICSP48669.2020.9321019","url":null,"abstract":"Track-before-detect algorithm is an effective solution of detecting and tracking a low signal-to-noise ratio (SNR) target whose amplitude distribution characteristic is needed as the prior information. Under the point target hypothesis in most previous works, the amplitude of target is usually assumed to be known or modeled as a state variable. However, these approaches cannot simply be migrated to the extended target tracking problem because of the unknown target extended length. This paper considers the issue of extended target joint detection and tracking with unknown amplitude distribution information through the use of Bernoulli particle filter based track-before-detect (BPF-TBD) methods. The proposed heuristic algorithm accumulates the multi-frame measurement data along the potential track of the target by a sliding window and then extracts the amplitude distribution information by means of principal component analysis (PCA) method. Simulation results show that the property of the proposed method asymptotically converges to the exact filter with prior correct expected amplitude distribution information, which indicates a superior performance in terms of feasibility and effectiveness.","PeriodicalId":237073,"journal":{"name":"2020 15th IEEE International Conference on Signal Processing (ICSP)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121907929","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: 0

A New Weighted Loss for Single Channel Speech Enhancement under Low Signal-to-Noise Ratio Environment 低信噪比环境下一种新的加权损失单通道语音增强方法

2020 15th IEEE International Conference on Signal Processing (ICSP) Pub Date : 2020-12-06 DOI: 10.1109/ICSP48669.2020.9320989

Jian Xiao, Hongqing Liu, Yi Zhou, Zhen Luo

引用次数: 0

The Design of Integrated Waveform Based on MSK-LFM Signal 基于MSK-LFM信号的集成波形设计

2020 15th IEEE International Conference on Signal Processing (ICSP) Pub Date : 2020-12-06 DOI: 10.1109/ICSP48669.2020.9320941

Wenxu Zhang, Heng Zhang

引用次数: 2

Identification of Ship and Corner Reflector In sea clutter environment 海杂波环境下舰船与角反射器的识别

2020 15th IEEE International Conference on Signal Processing (ICSP) Pub Date : 2020-12-06 DOI: 10.1109/ICSP48669.2020.9321063

Zhuorui Liang, Yong Wang, Xiaofeng Zhang, M. Xie, Xiongjun Fu

引用次数: 2

ESinGAN: Enhanced Single-Image GAN Using Pixel Attention Mechanism for Image Super-Resolution ESinGAN:基于像素注意机制的图像超分辨率增强单图像GAN

2020 15th IEEE International Conference on Signal Processing (ICSP) Pub Date : 2020-12-06 DOI: 10.1109/ICSP48669.2020.9320934

Wenyu Sun, Baodi Liu

引用次数: 5

A Bandpass Filter With Multi Deep Denoising Autoencoder for Hearing Applications 用于听力应用的带通滤波器和多深度去噪自动编码器

2020 15th IEEE International Conference on Signal Processing (ICSP) Pub Date : 2020-12-06 DOI: 10.1109/ICSP48669.2020.9320899

Raghad Yaseen Lazim, Xiaojun Wu

引用次数: 0