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<h2 id="有关行为识别的论文概括"><a name="有关行为识别的论文概括" href="#有关行为识别的论文概括"></a>有关行为识别的论文概括</h2><p class="toc" style="undefined"></p><ul>
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<a href="#有关行为识别的论文概括" title="有关行为识别的论文概括">有关行为识别的论文概括</a>
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<a href="#ijcai" title="IJCAI">IJCAI</a>
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<a href="#ubicomp-2014" title="Ubicomp 2014">Ubicomp 2014</a>
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<a href="#ubicomp-2013" title="Ubicomp 2013">Ubicomp 2013</a>
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<a href="#ubicomp-2012" title="Ubicomp 2012">Ubicomp 2012</a>
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<a href="#ubicmop-2011" title="Ubicmop 2011">Ubicmop 2011</a>
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<a href="#mobisys-2015" title="MobiSys 2015">MobiSys 2015</a>
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<a href="#mobisys-2014" title="MobiSys 2014">MobiSys 2014</a>
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<a href="#mobisys-2013" title="MobiSys 2013">MobiSys 2013</a>
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<a href="#mobisys-2012" title="MobiSys 2012">MobiSys 2012</a>
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<a href="#mobisys-2011" title="MobiSys 2011">MobiSys 2011</a>
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<p></p><ul>
<li><h3 id="ijcai"><a name="ijcai" href="#ijcai"></a>IJCAI</h3>
<ol>
<li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/IJCAI/IJCAI15-231.pdf">Action2Activity: Recognizing Complex Activities from Sensor Data</a><br>重新认识动作和行为，并提出新颖的方法来区分对待时序数据和行为的分解与合成理解</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/IJCAI/IJCAI15-561.pdf">Deep Convolutional Neural Networks On Multichannel Time Series or Human Activity Recognition</a><br>深度神经网络在行为识别中的应用</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/IJCAI/IJCAI11-228.pdf">Acivity Recognition with Finite State Machines</a><br>有限状态机理论在行为识别中。。。不太懂</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/IJCAI/IJCAI11-290.pdf">Feature Learning for Activity Recognition in Ubiquitous Computing</a><br>行为识别中的特征学习</p>
</li></ol>
</li><li><h3 id="ubicomp-2014"><a name="ubicomp-2014" href="#ubicomp-2014"></a>Ubicomp 2014</h3>
<ol>
<li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202014/p307-hernandez.pdf">Using Electrodermal Activity to Recognize Ease of Engagement in Children during Social Interactions</a><br>生理学传感器帮助发现儿童的社交行为，方便成人的管理</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202014/p307-hernandez.pdf">Pesuasive Technology to Improve Eating Behavior using a Sensor-Embedded Fork</a><br>发明一个智能感知的叉子帮助儿童吃饭、均衡饮食，利用讲故事和游戏的模式</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202014/p331-de_greef.pdf">BiliCam: Using Mobile Phones to Monitor Newborn Jaundice</a><br>用smartphone进行新生儿黄疸判断，判断皮肤的黄色污染</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202014/p373-sundholm.pdf">Smart-Mat: Recognizing and Counting Gym Exercises with Low-cost Resistive Pressure Sensing Matrix</a><br>用一个低成本的纺织传感器来进行压力传感，识别人体运动</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202014/p389-srinivasan.pdf">MobileMiner: Mining Your Frequent Patterns on Your Phone</a><br>用一个手机上的app来检测用户使用手机的行为，类似iOS9的siri</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202014/p425-du.pdf">Predicting Activity Attendance in Event-Based Social Networks: Content, Context and Social Influence</a><br>识别用户在社交网络中的行为，SVD-MFN</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202014/1407.0566.pdf">Money Walks: A Human-Centric Study on the Economics of Personal Mobile Data</a><br>通过手机来识别用户使用手机的行为</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202014/p649-gu.pdf">Intelligent Sleep Stage Mining Service with Smartphones</a><br>移动服务监测睡眠的不同阶段</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202014/p661-griffiths.pdf">Health Chair: Implicitly Sensing Heart and Respiratory Rate</a><br>智能椅子，通过扶手和椅背检测心跳和呼吸的频率</p>
</li></ol>
</li></ul><ul>
<li><h3 id="ubicomp-2013"><a name="ubicomp-2013" href="#ubicomp-2013"></a>Ubicomp 2013</h3>
<ol>
<li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202013/p143-murata.pdf">A Wearable Projector-based Gait Assistance System and its Application for Elderly People</a><br>用一个可穿戴的基于投影的设备来监测老人的步态</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202013/p193-killijian.pdf">SOUK: Social Observation of hUman Kinetics∗ </a><br>监测人群和位置和方向，很高的准确性</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202013/p197-bao.pdf">Your Reactions Suggest You Liked the Movie: Automatic Content Rating via Reaction Sensing</a><br>通过手机和平板上的传感器采集用户语音、与应用交互等的数据来判断用户对所看内容的评分</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202013/p225-brajdic.pdf">Walk Detection and Step Counting on Unconstrained Smartphones</a><br>通过智能手机监测人的行走方向和步数</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202013/p235-ladha.pdf">ClimbAX: Skill Assessment for Climbing Enthusiasts</a><br>一个监测登山者的行动并给出评价的系统</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202013/p245-sumida.pdf">Estimating Heart Rate Variation during Walking with Smartphone</a><br>用智能手机监测行走时的心跳</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202013/p335-shin.pdf">Automatically Detecting Problematic Use of Smartphones</a><br>监测用户使用手机的行为</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202013/p345-helaoui.pdf">A Probabilistic Ontological Framework for the Recognition of Multilevel Human Activities</a><br>利用一个概率模型感知多层次的人物行为</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202013/Zero Learning_Activity_UbiCopm13Notes.pdf">Towards Zero-Shot Learning for Human Activity Recognition Using Semantic Attribute Sequence Model</a><br>一种新的学习方式，语义属性序列模型，可以识别没有训练集或者未标记的数据和行为</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202013/p415-ladha.pdf">Dog’s Life: Wearable Activity Recognition for Dogs</a><br>在自然环境下通过项圈识别狗的行为</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202013/p459-ganti.pdf">Inferring Human Mobility Patterns from Taxicab Location Traces</a><br>从出租车定位装置推断人的行动轨迹</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202013/p647-tian.pdf">Understanding User Behavior at Scale in a Mobile Video Chat Application</a><br>分析聊天用户的行为挖掘</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202013/p721-zheng.pdf">An Unsupervised Learning Approach to Social Circles Detection in Ego Bluetooth Proximity Network</a><br>用蓝牙推断用户的社交圈子</p>
</li></ol>
</li><li><h3 id="ubicomp-2012"><a name="ubicomp-2012" href="#ubicomp-2012"></a>Ubicomp 2012</h3>
<ol>
<li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p113-park.pdf">Onine Pose Classification and Walking Speed Estimation using Handheld Devices</a><br>用手持设备进行手势分类和行动速度的估计</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/2012-Thomaz-RWAHTIS.pdf">Recognizing Water-Based Activities in the Home Through Infrastructure-Mediated Sensing</a><br>通过用水行为来判断用户的实际行为，比如在做饭还是在洗澡</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/cohn12.pdf">An Ultra-Low-Power Human Body Motion Sensor Using Static Electric Field Sensing</a><br>介绍一种新的低功耗的能感知用户行为的传感器</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p153-zheng.pdf">An Unsupervised Framework for Sensing Individual and Cluster Behavior Patterns From Human Mobile Data</a><br>介绍一种非监督式感知个人和群体行为的框架</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p163-do.pdf">Contextual Conditional Models for Smartphone-based Human Mobility Prediction</a><br>上下文挖掘用户行为，并进行位置预测、持续时间预测</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p208-lei.pdf">Fine-Grained Kitchen Activity Recognition using RGB-D</a><br>用rgb和深度摄像头来追踪人体行为，实现厨房行为的监测</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p250-berlin.pdf">detecting Leisure Activities with Dense Motif Discovery</a><br>用密度主题发现的方法来发现用户的行为模式</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p240-kjaergaard.pdf">Detecting Pedestrian Flocks by Fusion of Multi-Modal Sensors in Mobile Phones</a><br>多种传感器感知群体行为，进行层次化聚类</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p270-hong.pdf">Understanding Physiological Responses to Stressors during Physical Activity</a><br>用传感器理解人体物理行动，解释做出这些行动的原因</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p280-larson.pdf">SpiroSmart: Using a Microphone to MeasureLung Function on a Mobile Phone</a><br>用手机麦克风检测人体肺的功能</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p290-sun.pdf">A high accuracy, low-latency, scalable microphone-array system for conversation analysis</a><br>用手机麦克风理解对话情景</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p301-hernandez.pdf">Mood Meter: Counting Smiles in the Wild</a><br>监测校园人脸</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p311-coutrix.pdf">Identifying Emotions Expressed by Mobile Users through 2D Surface and 3D Motion Gestures</a><br>用移动设备检测用户的情绪，便宜，有效</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p341-yatani.pdf">BodyScope: A Wearable Acoustic Sensorfor Activity Recognition</a><br>一个通过声音来对人体喉咙行为（吃、喝、说话、笑等）进行分类的穿戴设备</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p341-yatani.pdf">StressSense: Detecting Stress in Unconstrained Acoustic Environments using Smartphones</a><br>通过麦克风来检测人是否有stress</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p401-marcu.pdf">Parent-Driven Use of Wearable Cameras for Autism Support: A Field Study with Families</a><br>通过给孩子佩戴一个camera来用孩子的视角看世界，帮助了解自闭症儿童的行为</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p411-fan.pdf">Augmenting Gesture Recognition with Erlang-Cox Models To Identify Neurological Disorders in Premature Babies</a><br>传感器检测新生儿的脑中风</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p491-bao.pdf">Helping Mobile Apps Bootstrap with Fewer Users</a><br>通过行为聚类来解决app冷启动没有数据的问题</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p537-ouchi.pdf">Indoor-Outdoor Activity Recognition by a Smartphone</a><br>智能手机识别室内和室外活动</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p576-beltran-marquez.pdf">Activity Recognition Using a Spectral Entropy Signature</a><br>分析声音信号的光谱识别人的行为</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p633-hoque.pdf">Semantic Anomaly Detection in Daily Activities</a><br>通过语义来识别人的日常行动</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p647-ranjan.pdf">Using mid-range RFID for location based activity recognition</a><br>RFID进行基于位置的行为识别</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p645-uchida.pdf">Preliminary Evaluation of Feature Level Compensation for Missing Data in Multi-sensor Activity Recognition</a><br>多种机器学习算法来进行多传感器的行为识别</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p661-kao.pdf">Phone-based Gait Analysis to Detect Alcohol Usage</a><br>用智能手机进行步态鉴别，进而检测喝酒的时间</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p711-vaitukaitis.pdf">Eye Gesture Recognition on Portable Devices</a><br>便携设备识别眼球运动</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202012/p745-zhang.pdf">A Preliminary Study of Sensing Appliance Usage for Human Activity Recognition Using Mobile Magnetometer</a><br>用手机的磁力计感知人在家庭的行为</p>
</li></ol>
</li><li><h3 id="ubicmop-2011"><a name="ubicmop-2011" href="#ubicmop-2011"></a>Ubicmop 2011</h3>
<ol>
<li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202011/p1-tsujita.pdf">Smiling Makes Us Happier: Enhancing Positive Mood and Communication with Smile-Encouraging Digital Appliances</a><br>一个测试微笑并统计日常微笑的装置，帮助你微笑，保持好心情哦！</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202011/p119-strohrmann.pdf">CoDine: An Interactive Multi-sensory System for Remote Dining</a><br>一个餐桌上用kinect进行远程交互的产品</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202011/p21-wei.pdf">Out of the Lab and Into the Woods: Kinematic Analysis in Running Using Wearable Sensors</a><br>给运动员装上可穿戴设备传感器</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202011/p271-jiang.pdf">MAQS: A Personalized Mobile Sensing System for Indoor Air Quality Monitoring</a><br>移动应用测室内空气质量</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202011/p445-aharony.pdf">The Social fMRI: Measuring, Understanding, and Designing Social Mechanisms in the Real World</a><br>移动装置帮助收集数据</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202011/p543-chen.pdf">ARHCI: Use Input and Output of Eyes to Interact with Things</a><br>用AR的方式来进行检测眼球运动并用HCI的方式进行反馈</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202011/p559-shi.pdf">A Rotation Based Method for Detecting On-body Positions of Mobile Devices</a><br>一种新的算法，用来检测移动设备相对于人体的位置</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202011/p567-tsai.pdf">Polite Ringer II: A Ringtone Interaction System Using Sensor Fusion</a><br>智能手机来电时的铃声很吵，这个系统可能用机器学习的方法识别人体活动，从而自动减小铃声</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202011/p589-ohmura.pdf">Response Time Improvement in Accelerometer-based Activity Recognition by Activity Change Detection</a><br>通过检测运动数据中的变点来缩短机器学习反应的时间</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202011/p591-grokop.pdf">Activity and Device Position Recognition In Mobile Devices</a><br>在安卓设备上进行行为识别和移动设备在手中的位置的识别</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/Ubicomp%202011/p603-kawaguchi.pdf">Distributed Human Activity Data Processing using HASC Tool</a><br>使用分布式系统加快行为识别的数据处理速度</p>
</li></ol>
</li><li><h3 id="mobisys-2015"><a name="mobisys-2015" href="#mobisys-2015"></a>MobiSys 2015</h3>
<ol>
<li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202015/p15-yun.pdf">Turning a Mobile Device into a Mouse in the Air</a><br>用智能手机等智能设备来模拟鼠标，较精确</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202015/p227-nirjon.pdf">Tracking Keystrokes Using Wireless Signals</a><br>无线信号追踪按键</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202015/p257-jain.pdf">Contactless Sleep Apnea Detection on Smartphones</a><br>智能手机监测睡眠窒息</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202015/p31-chen.pdf">TypingRing: A Wearable Ring Platform for Text Input</a><br>在中指上戴戒指实现输入，速度和准确率不错</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202015/p45-nandakumar.pdf">LookUp: Enabling Pedestrian Safety Services via Shoe Sensing</a><br>鞋上的传感器实现监测变道</p>
</li></ol>
</li><li><h3 id="mobisys-2014"><a name="mobisys-2014" href="#mobisys-2014"></a>MobiSys 2014</h3>
<ol>
<li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202014/p2-rahman.pdf">BodyBeat: A Mobile System for Sensing Non-Speech Body Sounds</a><br>基于ARM的传感器，麦克风，安卓手机，检测非说话的声音</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202014/p42-wang.pdf">Tracking Human Queues Using Single-Point Signal Monitoring</a><br>用wifi信号来追踪人群排队，推算等待时间</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202014/p55-cornelius.pdf">A Wearable System That Knows Who Wears It</a><br>传感器感知谁穿了它并且它确实是在被穿着</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202014/p68-ha.pdf">Towards Wearable Cognitive Assistance</a><br>用google glass帮助认知</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202014/p82-mayberry.pdf">iShadow: Design of a Wearable, Real-Time Mobile Gaze Tracker</a><br>追踪眼球运动</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202014/p149-parate.pdf">RisQ: Recognizing Smoking Gestures with Inertial Sensors on a Wristband</a><br>用手环上的9轴惯性传感器检测吸烟动作，精确度较高</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202014/p162-gummeson.pdf">An Energy Harvesting Wearable Ring Platform for Gesture Input on Surfaces</a><br>食指上带戒指进行输入</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202014/p329-roy.pdf">I am a Smartphone and I can Tell my User’s Walking Direction</a><br>智能手机上的传感器判断用户行走的方向</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202014/p379-park.pdf">Poster: Ontology-Based Heartbeat Classification for Mobile Electrocardiogram Monitoring</a><br>智能手机进行心跳分类，检测心率失常</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202014/p372-ho.pdf">Poster: M-SEven: Monitoring Smoking Event by Considering Time Sequence Information via iPhone M7 API</a><br>用iPhone的协处理器监测是否吸烟</p>
</li></ol>
</li><li><h3 id="mobisys-2013"><a name="mobisys-2013" href="#mobisys-2013"></a>MobiSys 2013</h3>
<ol>
<li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202013/p361-cheng.pdf">NuActiv: Recognizing Unseen New Activities Using Semantic Attribute-Based Learning</a><br>语义属性为基础来识别未知的活动</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202013/p389-likamwa.pdf">MoodScope: Building a Mood Sensor from Smartphone Usage Patterns</a><br>手机中建立一个软件，利用通话记录等判断人的情绪</p>
</li><li><p><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202013/p403-nirjon.pdf">Auditeur: A Mobile-Cloud Service Platform for Acoustic Event Detection on Smartphones</a><br>基于云的平台，进行声音事件的检测，很开放，很好用</p>
</li></ol>
</li><li><h3 id="mobisys-2012"><a name="mobisys-2012" href="#mobisys-2012"></a>MobiSys 2012</h3>
<ol>
<li><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202012/p113-yan.pdf">Fast App Launching for Mobile Devices Using Predictive User Context</a><br>智能手机根据用户的位置喜好习惯等信息，进行预处理，加快打开app的速度</li></ol>
</li></ul><ul>
<li><h3 id="mobisys-2011"><a name="mobisys-2011" href="#mobisys-2011"></a>MobiSys 2011</h3>
<ol>
<li><a href="https://github.com/jindongwang/MachineLearning/blob/master/papers%20about%20activity%20recognition/MobiSys%202011/p15-agrawal.pdf">Using Mobile Phones to Write in Air</a><br>在诺基亚N95上实现用手机写字母的识别和单词的识别，效果不错，不过太慢了吧。。。</li></ol>
</li></ul>
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