diff --git a/ui/app.js b/ui/app.js index a1c94ded..12b7df1a 100644 --- a/ui/app.js +++ b/ui/app.js @@ -10,11 +10,65 @@ import { wsService } from './services/websocket.service.js'; import { healthService } from './services/health.service.js'; import { sensingService } from './services/sensing.service.js'; import { backendDetector } from './utils/backend-detector.js'; +import { i18n } from './i18n/index.js'; +import zhCN from './i18n/locales/zh-CN.js'; +import enUS from './i18n/locales/en-US.js'; class WiFiDensePoseApp { constructor() { this.components = {}; this.isInitialized = false; + this.i18n = i18n; + } + + /** + * 初始化国际化模块 + */ + initializeI18n() { + i18n.register('zh-CN', zhCN); + i18n.register('en-US', enUS); + const locale = i18n.init(); + console.log(`[App] i18n initialized with locale: ${locale}`); + + i18n.onLocaleChange(() => { + i18n.updateDOM(); + }); + + i18n.updateDOM(); + } + + /** + * 获取当前语言 + * @returns {string} 当前语言代码 + */ + getLocale() { + return i18n.getLocale(); + } + + /** + * 设置语言 + * @param {string} locale - 语言代码 + */ + setLocale(locale) { + i18n.setLocale(locale); + } + + /** + * 获取可用语言列表 + * @returns {string[]} 语言代码数组 + */ + getAvailableLocales() { + return i18n.getAvailableLocales(); + } + + /** + * 翻译文本 + * @param {string} key - 翻译键 + * @param {Object} params - 参数 + * @returns {string} 翻译后的文本 + */ + t(key, params = {}) { + return i18n.t(key, params); } // Initialize application @@ -22,6 +76,9 @@ class WiFiDensePoseApp { try { console.log('Initializing WiFi DensePose UI...'); + // Initialize i18n first + this.initializeI18n(); + // Set up error handling this.setupErrorHandling(); @@ -39,7 +96,7 @@ class WiFiDensePoseApp { } catch (error) { console.error('Failed to initialize application:', error); - this.showGlobalError('Failed to initialize application. Please refresh the page.'); + this.showGlobalError(i18n.t('errors.initFailed')); } } @@ -227,6 +284,22 @@ class WiFiDensePoseApp { window.addEventListener('beforeunload', () => { this.cleanup(); }); + + // Handle language selector + this.setupLanguageSelector(); + } + + /** + * 设置语言选择器 + */ + setupLanguageSelector() { + const selector = document.getElementById('languageSelector'); + if (selector) { + selector.value = i18n.getLocale(); + selector.addEventListener('change', (e) => { + i18n.setLocale(e.target.value); + }); + } } // Handle window resize diff --git a/ui/i18n/index.js b/ui/i18n/index.js new file mode 100644 index 00000000..f333d2bf --- /dev/null +++ b/ui/i18n/index.js @@ -0,0 +1,238 @@ +/** + * @file i18n 核心模块 - 提供国际化语言支持 + * @description 轻量级国际化解决方案,支持多语言切换、参数插值、嵌套翻译 + */ + +const DEFAULT_LOCALE = 'en-US'; +const STORAGE_KEY = 'wifi-densepose-locale'; + +class I18n { + constructor() { + this.currentLocale = DEFAULT_LOCALE; + this.translations = new Map(); + this.fallbackLocale = DEFAULT_LOCALE; + this.observers = new Set(); + } + + /** + * 注册语言包 + * @param {string} locale - 语言代码 (如 'zh-CN', 'en-US') + * @param {Object} messages - 翻译消息对象 + */ + register(locale, messages) { + if (!locale || typeof locale !== 'string') { + console.error('[I18n] Invalid locale:', locale); + return; + } + this.translations.set(locale, messages); + console.log(`[I18n] Registered locale: ${locale}`); + } + + /** + * 设置当前语言 + * @param {string} locale - 语言代码 + */ + setLocale(locale) { + if (!this.translations.has(locale)) { + console.warn(`[I18n] Locale "${locale}" not registered, using fallback`); + locale = this.fallbackLocale; + } + + const oldLocale = this.currentLocale; + this.currentLocale = locale; + + try { + localStorage.setItem(STORAGE_KEY, locale); + } catch (e) { + console.warn('[I18n] Failed to save locale to localStorage'); + } + + document.documentElement.lang = locale.split('-')[0]; + + this.observers.forEach(callback => { + try { + callback(locale, oldLocale); + } catch (e) { + console.error('[I18n] Observer callback error:', e); + } + }); + + console.log(`[I18n] Locale changed: ${oldLocale} -> ${locale}`); + } + + /** + * 获取当前语言 + * @returns {string} 当前语言代码 + */ + getLocale() { + return this.currentLocale; + } + + /** + * 获取所有已注册的语言列表 + * @returns {string[]} 语言代码数组 + */ + getAvailableLocales() { + return Array.from(this.translations.keys()); + } + + /** + * 初始化语言设置 + * @returns {string} 检测到的语言代码 + */ + init() { + let savedLocale = null; + + try { + savedLocale = localStorage.getItem(STORAGE_KEY); + } catch (e) { + console.warn('[I18n] Failed to read locale from localStorage'); + } + + if (savedLocale && this.translations.has(savedLocale)) { + this.currentLocale = savedLocale; + } else { + const browserLocale = this.detectBrowserLocale(); + this.currentLocale = browserLocale; + } + + document.documentElement.lang = this.currentLocale.split('-')[0]; + console.log(`[I18n] Initialized with locale: ${this.currentLocale}`); + + return this.currentLocale; + } + + /** + * 检测浏览器语言 + * @returns {string} 检测到的语言代码 + */ + detectBrowserLocale() { + const browserLang = navigator.language || navigator.userLanguage; + + if (this.translations.has(browserLang)) { + return browserLang; + } + + const baseLang = browserLang.split('-')[0]; + for (const locale of this.translations.keys()) { + if (locale.startsWith(baseLang)) { + return locale; + } + } + + return this.fallbackLocale; + } + + /** + * 翻译文本 + * @param {string} key - 翻译键,支持点分隔符嵌套 (如 'nav.dashboard') + * @param {Object} params - 插值参数 + * @returns {string} 翻译后的文本 + */ + t(key, params = {}) { + const messages = this.translations.get(this.currentLocale); + let text = this.getNestedValue(messages, key); + + if (text === undefined) { + const fallbackMessages = this.translations.get(this.fallbackLocale); + text = this.getNestedValue(fallbackMessages, key); + } + + if (text === undefined) { + console.warn(`[I18n] Missing translation for key: "${key}"`); + return key; + } + + if (typeof text === 'string' && Object.keys(params).length > 0) { + text = this.interpolate(text, params); + } + + return text; + } + + /** + * 获取嵌套对象的值 + * @param {Object} obj - 源对象 + * @param {string} key - 点分隔的键路径 + * @returns {*} 找到的值或 undefined + */ + getNestedValue(obj, key) { + if (!obj || typeof key !== 'string') return undefined; + + const keys = key.split('.'); + let value = obj; + + for (const k of keys) { + if (value && typeof value === 'object' && k in value) { + value = value[k]; + } else { + return undefined; + } + } + + return value; + } + + /** + * 插值替换参数 + * @param {string} text - 包含 {param} 占位符的文本 + * @param {Object} params - 参数对象 + * @returns {string} 替换后的文本 + */ + interpolate(text, params) { + return text.replace(/\{(\w+)\}/g, (match, key) => { + return params.hasOwnProperty(key) ? String(params[key]) : match; + }); + } + + /** + * 监听语言变化 + * @param {Function} callback - 回调函数 (newLocale, oldLocale) => void + * @returns {Function} 取消监听函数 + */ + onLocaleChange(callback) { + this.observers.add(callback); + return () => this.observers.delete(callback); + } + + /** + * 更新页面中所有带有 data-i18n 属性的元素 + */ + updateDOM() { + const elements = document.querySelectorAll('[data-i18n]'); + + elements.forEach(element => { + const key = element.getAttribute('data-i18n'); + const attr = element.getAttribute('data-i18n-attr') || 'textContent'; + const params = element.getAttribute('data-i18n-params'); + + let parsedParams = {}; + if (params) { + try { + parsedParams = JSON.parse(params); + } catch (e) { + console.warn('[I18n] Failed to parse params:', params); + } + } + + const text = this.t(key, parsedParams); + + if (attr === 'textContent') { + element.textContent = text; + } else if (attr === 'innerHTML') { + element.innerHTML = text; + } else if (attr === 'placeholder') { + element.placeholder = text; + } else if (attr === 'title') { + element.title = text; + } else { + element.setAttribute(attr, text); + } + }); + } +} + +const i18n = new I18n(); + +export { i18n, I18n }; +export default i18n; diff --git a/ui/i18n/locales/en-US.js b/ui/i18n/locales/en-US.js new file mode 100644 index 00000000..8b0ea4cb --- /dev/null +++ b/ui/i18n/locales/en-US.js @@ -0,0 +1,287 @@ +/** + * @file English (US) Language Pack + * @description WiFi DensePose Application English Translation + */ + +export default { + meta: { + title: 'WiFi DensePose: Human Tracking Through Walls', + description: 'Human Tracking Through Walls Using WiFi Signals' + }, + + header: { + title: 'WiFi DensePose', + subtitle: 'Human Tracking Through Walls Using WiFi Signals' + }, + + nav: { + dashboard: 'Dashboard', + hardware: 'Hardware', + demo: 'Live Demo', + architecture: 'Architecture', + performance: 'Performance', + applications: 'Applications', + sensing: 'Sensing', + training: 'Training', + observatory: 'Observatory' + }, + + dashboard: { + title: 'Revolutionary WiFi-Based Human Pose Detection', + description: 'AI can track your full-body movement through walls using just WiFi signals. Researchers at Carnegie Mellon have trained a neural network to turn basic WiFi signals into detailed wireframe models of human bodies.', + + status: { + title: 'System Status', + apiServer: 'API Server', + hardware: 'Hardware', + inference: 'Inference', + streaming: 'Streaming', + datasource: 'Data Source' + }, + + metrics: { + title: 'System Metrics', + cpuUsage: 'CPU Usage', + memoryUsage: 'Memory Usage', + diskUsage: 'Disk Usage' + }, + + features: { + title: 'Features' + }, + + stats: { + title: 'Live Statistics', + activePersons: 'Active Persons', + avgConfidence: 'Avg Confidence', + totalDetections: 'Total Detections', + zoneOccupancy: 'Zone Occupancy' + }, + + benefits: { + throughWalls: { + title: 'Through Walls', + description: 'Works through solid barriers with no line of sight required' + }, + privacy: { + title: 'Privacy-Preserving', + description: 'No cameras or visual recording - just WiFi signal analysis' + }, + realtime: { + title: 'Real-Time', + description: 'Maps 24 body regions in real-time at 100Hz sampling rate' + }, + lowCost: { + title: 'Low Cost', + description: 'Built using $30 commercial WiFi hardware' + } + }, + + systemStats: { + bodyRegions: 'Body Regions', + samplingRate: 'Sampling Rate', + accuracy: 'Accuracy (AP@50)', + hardwareCost: 'Hardware Cost' + } + }, + + hardware: { + title: 'Hardware Configuration', + + antenna: { + title: '3×3 Antenna Array', + helpText: 'Click antennas to toggle their state', + transmitters: 'Transmitters (3)', + receivers: 'Receivers (6)' + }, + + wifi: { + title: 'WiFi Configuration', + frequency: 'Frequency', + frequencyValue: '2.4GHz ± 20MHz', + subcarriers: 'Subcarriers', + subcarriersValue: '30', + samplingRate: 'Sampling Rate', + samplingRateValue: '100 Hz', + totalCost: 'Total Cost', + totalCostValue: '$30' + }, + + csi: { + title: 'Real-time CSI Data', + amplitude: 'Amplitude', + phase: 'Phase' + } + }, + + demo: { + title: 'Live Demonstration', + + controls: { + startStream: 'Start Stream', + stopStream: 'Stop Stream', + ready: 'Ready' + }, + + signal: { + title: 'WiFi Signal Analysis', + signalStrength: 'Signal Strength', + processingLatency: 'Processing Latency' + }, + + pose: { + title: 'Human Pose Detection', + personsDetected: 'Persons Detected', + confidence: 'Confidence', + keypoints: 'Keypoints' + } + }, + + architecture: { + title: 'System Architecture', + + steps: { + csiInput: { + title: 'CSI Input', + description: 'Channel State Information collected from WiFi antenna array' + }, + phaseSanitization: { + title: 'Phase Sanitization', + description: 'Remove hardware-specific noise and normalize signal phase' + }, + modalityTranslation: { + title: 'Modality Translation', + description: 'Convert WiFi signals to visual representation using CNN' + }, + densePose: { + title: 'DensePose-RCNN', + description: 'Extract human pose keypoints and body part segmentation' + }, + wireframeOutput: { + title: 'Wireframe Output', + description: 'Generate final human pose wireframe visualization' + } + } + }, + + performance: { + title: 'Performance Analysis', + + wifiBased: { + title: 'WiFi-based (Same Layout)', + averagePrecision: 'Average Precision', + ap50: 'AP@50', + ap75: 'AP@75' + }, + + imageBased: { + title: 'Image-based (Reference)', + averagePrecision: 'Average Precision', + ap50: 'AP@50', + ap75: 'AP@75' + }, + + advantages: { + title: 'Advantages & Limitations', + pros: { + title: 'Advantages', + items: [ + 'Through-wall detection', + 'Privacy preserving', + 'Lighting independent', + 'Low cost hardware', + 'Uses existing WiFi' + ] + }, + cons: { + title: 'Limitations', + items: [ + 'Performance drops in different layouts', + 'Requires WiFi-compatible devices', + 'Training requires synchronized data' + ] + } + } + }, + + applications: { + title: 'Real-World Applications', + + elderlyCare: { + title: 'Elderly Care Monitoring', + description: 'Monitor elderly individuals for falls or emergencies without invading privacy. Track movement patterns and detect anomalies in daily routines.', + features: ['Fall Detection', 'Activity Monitoring', 'Emergency Alert'] + }, + + homeSecurity: { + title: 'Home Security Systems', + description: 'Detect intruders and monitor home security without visible cameras. Track multiple persons and identify suspicious movement patterns.', + features: ['Intrusion Detection', 'Multi-person Tracking', 'Invisible Monitoring'] + }, + + healthcare: { + title: 'Healthcare Patient Monitoring', + description: 'Monitor patients in hospitals and care facilities. Track vital signs through movement analysis and detect health emergencies.', + features: ['Vital Sign Analysis', 'Movement Tracking', 'Health Alerts'] + }, + + smartBuilding: { + title: 'Smart Building Occupancy', + description: 'Optimize building energy consumption by tracking occupancy patterns. Control lighting, HVAC, and security systems automatically.', + features: ['Energy Optimization', 'Occupancy Tracking', 'Smart Controls'] + }, + + arVr: { + title: 'AR/VR Applications', + description: 'Enable full-body tracking for virtual and augmented reality applications without wearing additional sensors or cameras.', + features: ['Full Body Tracking', 'Sensor-free', 'Immersive Experience'] + }, + + implementation: { + title: 'Implementation Considerations', + description: 'While WiFi DensePose offers revolutionary capabilities, successful implementation requires careful consideration of environment setup, data privacy regulations, and system calibration for optimal performance.' + } + }, + + training: { + title: 'Model Training', + description: 'Record CSI data, train pose estimation models, and manage .rvf files' + }, + + common: { + loading: 'Loading...', + error: 'Error', + success: 'Success', + warning: 'Warning', + info: 'Info', + confirm: 'Confirm', + cancel: 'Cancel', + save: 'Save', + delete: 'Delete', + edit: 'Edit', + add: 'Add', + search: 'Search', + noData: 'No data available', + retry: 'Retry', + close: 'Close', + back: 'Back', + next: 'Next', + previous: 'Previous', + submit: 'Submit', + reset: 'Reset' + }, + + errors: { + initFailed: 'Failed to initialize application. Please refresh the page.', + unexpectedError: 'An unexpected error occurred', + connectionLost: 'Connection lost', + backendUnavailable: 'Backend unavailable — start sensing-server' + }, + + notifications: { + mockServerActive: 'Mock server active - testing mode', + connectedToBackend: 'Connected to Rust sensing server', + pageHidden: 'Page hidden, pausing updates', + pageVisible: 'Page visible, resuming updates' + } +}; diff --git a/ui/i18n/locales/zh-CN.js b/ui/i18n/locales/zh-CN.js new file mode 100644 index 00000000..68f73e09 --- /dev/null +++ b/ui/i18n/locales/zh-CN.js @@ -0,0 +1,287 @@ +/** + * @file 中文简体语言包 + * @description WiFi DensePose 应用中文简体翻译 + */ + +export default { + meta: { + title: 'WiFi DensePose: 穿墙人体追踪', + description: '使用 WiFi 信号进行穿墙人体追踪' + }, + + header: { + title: 'WiFi DensePose', + subtitle: '使用 WiFi 信号进行穿墙人体追踪' + }, + + nav: { + dashboard: '仪表盘', + hardware: '硬件配置', + demo: '实时演示', + architecture: '系统架构', + performance: '性能分析', + applications: '应用场景', + sensing: '感知', + training: '模型训练', + observatory: '观测站' + }, + + dashboard: { + title: '革命性的 WiFi 人体姿态检测', + description: 'AI 可以仅使用 WiFi 信号穿透墙壁追踪您的全身动作。卡内基梅隆大学的研究人员训练了一个神经网络,可以将基本的 WiFi 信号转换为详细的人体线框模型。', + + status: { + title: '系统状态', + apiServer: 'API 服务器', + hardware: '硬件', + inference: '推理引擎', + streaming: '数据流', + datasource: '数据源' + }, + + metrics: { + title: '系统指标', + cpuUsage: 'CPU 使用率', + memoryUsage: '内存使用率', + diskUsage: '磁盘使用率' + }, + + features: { + title: '功能特性' + }, + + stats: { + title: '实时统计', + activePersons: '活动人数', + avgConfidence: '平均置信度', + totalDetections: '总检测次数', + zoneOccupancy: '区域占用' + }, + + benefits: { + throughWalls: { + title: '穿墙检测', + description: '无需视线,可穿透实体障碍物工作' + }, + privacy: { + title: '隐私保护', + description: '无需摄像头或视频录制,仅分析 WiFi 信号' + }, + realtime: { + title: '实时处理', + description: '以 100Hz 采样率实时映射 24 个身体区域' + }, + lowCost: { + title: '低成本', + description: '使用价值 30 美元的商用 WiFi 硬件构建' + } + }, + + systemStats: { + bodyRegions: '身体区域', + samplingRate: '采样率', + accuracy: '准确率 (AP@50)', + hardwareCost: '硬件成本' + } + }, + + hardware: { + title: '硬件配置', + + antenna: { + title: '3×3 天线阵列', + helpText: '点击天线切换其状态', + transmitters: '发射器 (3)', + receivers: '接收器 (6)' + }, + + wifi: { + title: 'WiFi 配置', + frequency: '频率', + frequencyValue: '2.4GHz ± 20MHz', + subcarriers: '子载波', + subcarriersValue: '30', + samplingRate: '采样率', + samplingRateValue: '100 Hz', + totalCost: '总成本', + totalCostValue: '$30' + }, + + csi: { + title: '实时 CSI 数据', + amplitude: '幅度', + phase: '相位' + } + }, + + demo: { + title: '实时演示', + + controls: { + startStream: '开始流', + stopStream: '停止流', + ready: '就绪' + }, + + signal: { + title: 'WiFi 信号分析', + signalStrength: '信号强度', + processingLatency: '处理延迟' + }, + + pose: { + title: '人体姿态检测', + personsDetected: '检测到的人数', + confidence: '置信度', + keypoints: '关键点' + } + }, + + architecture: { + title: '系统架构', + + steps: { + csiInput: { + title: 'CSI 输入', + description: '从 WiFi 天线阵列收集信道状态信息' + }, + phaseSanitization: { + title: '相位净化', + description: '去除硬件特定噪声并归一化信号相位' + }, + modalityTranslation: { + title: '模态转换', + description: '使用 CNN 将 WiFi 信号转换为视觉表示' + }, + densePose: { + title: 'DensePose-RCNN', + description: '提取人体姿态关键点和身体部位分割' + }, + wireframeOutput: { + title: '线框输出', + description: '生成最终的人体姿态线框可视化' + } + } + }, + + performance: { + title: '性能分析', + + wifiBased: { + title: '基于 WiFi (相同布局)', + averagePrecision: '平均精度', + ap50: 'AP@50', + ap75: 'AP@75' + }, + + imageBased: { + title: '基于图像 (参考)', + averagePrecision: '平均精度', + ap50: 'AP@50', + ap75: 'AP@75' + }, + + advantages: { + title: '优势与局限', + pros: { + title: '优势', + items: [ + '穿墙检测', + '隐私保护', + '不受光照影响', + '低成本硬件', + '利用现有 WiFi' + ] + }, + cons: { + title: '局限', + items: [ + '不同布局下性能下降', + '需要兼容 WiFi 的设备', + '训练需要同步数据' + ] + } + } + }, + + applications: { + title: '实际应用场景', + + elderlyCare: { + title: '老年人监护', + description: '在不侵犯隐私的情况下监测老年人的跌倒或紧急情况。追踪活动模式并检测日常行为异常。', + features: ['跌倒检测', '活动监测', '紧急报警'] + }, + + homeSecurity: { + title: '家庭安防系统', + description: '无需可见摄像头即可检测入侵者并监控家庭安全。追踪多人并识别可疑行为模式。', + features: ['入侵检测', '多人追踪', '隐形监控'] + }, + + healthcare: { + title: '医疗患者监护', + description: '在医院和护理机构监测患者。通过动作分析追踪生命体征并检测健康紧急情况。', + features: ['生命体征分析', '动作追踪', '健康警报'] + }, + + smartBuilding: { + title: '智能建筑占用', + description: '通过追踪占用模式优化建筑能耗。自动控制照明、暖通空调和安防系统。', + features: ['节能优化', '占用追踪', '智能控制'] + }, + + arVr: { + title: 'AR/VR 应用', + description: '为虚拟和增强现实应用实现全身追踪,无需佩戴额外传感器或摄像头。', + features: ['全身追踪', '无传感器', '沉浸体验'] + }, + + implementation: { + title: '实施注意事项', + description: '虽然 WiFi DensePose 提供了革命性的能力,但成功实施需要仔细考虑环境设置、数据隐私法规和系统校准以获得最佳性能。' + } + }, + + training: { + title: '模型训练', + description: '记录 CSI 数据、训练姿态估计模型并管理 .rvf 文件' + }, + + common: { + loading: '加载中...', + error: '错误', + success: '成功', + warning: '警告', + info: '信息', + confirm: '确认', + cancel: '取消', + save: '保存', + delete: '删除', + edit: '编辑', + add: '添加', + search: '搜索', + noData: '暂无数据', + retry: '重试', + close: '关闭', + back: '返回', + next: '下一步', + previous: '上一步', + submit: '提交', + reset: '重置' + }, + + errors: { + initFailed: '应用初始化失败,请刷新页面。', + unexpectedError: '发生意外错误', + connectionLost: '连接已断开', + backendUnavailable: '后端不可用 — 请启动 sensing-server' + }, + + notifications: { + mockServerActive: '模拟服务器已激活 - 测试模式', + connectedToBackend: '已连接到 Rust 感知服务器', + pageHidden: '页面隐藏,暂停更新', + pageVisible: '页面可见,恢复更新' + } +}; diff --git a/ui/index.html b/ui/index.html index 59b4671e..5693971e 100644 --- a/ui/index.html +++ b/ui/index.html @@ -3,40 +3,44 @@
-Human Tracking Through Walls Using WiFi Signals
+Human Tracking Through Walls Using WiFi Signals
+
AI can track your full-body movement through walls using just WiFi signals. Researchers at Carnegie Mellon have trained a neural network to turn basic WiFi signals into detailed wireframe models of human bodies. @@ -47,30 +51,30 @@
Works through solid barriers with no line of sight required
+Works through solid barriers with no line of sight required
No cameras or visual recording - just WiFi signal analysis
+No cameras or visual recording - just WiFi signal analysis
Maps 24 body regions in real-time at 100Hz sampling rate
+Maps 24 body regions in real-time at 100Hz sampling rate
Built using $30 commercial WiFi hardware
+Built using $30 commercial WiFi hardware
Click antennas to toggle their state
+Click antennas to toggle their state
System Architecture
Channel State Information collected from WiFi antenna array
+Channel State Information collected from WiFi antenna array
Remove hardware-specific noise and normalize signal phase
+Remove hardware-specific noise and normalize signal phase
Convert WiFi signals to visual representation using CNN
+Convert WiFi signals to visual representation using CNN
Extract human pose keypoints and body part segmentation
+Extract human pose keypoints and body part segmentation
Generate final human pose wireframe visualization
+Generate final human pose wireframe visualization
Performance Analysis
Monitor elderly individuals for falls or emergencies without invading privacy. Track movement patterns and detect anomalies in daily routines.
+Monitor elderly individuals for falls or emergencies without invading privacy. Track movement patterns and detect anomalies in daily routines.
Detect intruders and monitor home security without visible cameras. Track multiple persons and identify suspicious movement patterns.
+Detect intruders and monitor home security without visible cameras. Track multiple persons and identify suspicious movement patterns.
Monitor patients in hospitals and care facilities. Track vital signs through movement analysis and detect health emergencies.
+Monitor patients in hospitals and care facilities. Track vital signs through movement analysis and detect health emergencies.
Optimize building energy consumption by tracking occupancy patterns. Control lighting, HVAC, and security systems automatically.
+Optimize building energy consumption by tracking occupancy patterns. Control lighting, HVAC, and security systems automatically.
Enable full-body tracking for virtual and augmented reality applications without wearing additional sensors or cameras.
+Enable full-body tracking for virtual and augmented reality applications without wearing additional sensors or cameras.
While WiFi DensePose offers revolutionary capabilities, successful implementation requires careful consideration of environment setup, data privacy regulations, and system calibration for optimal performance.
+While WiFi DensePose offers revolutionary capabilities, successful implementation requires careful consideration of environment setup, data privacy regulations, and system calibration for optimal performance.
Record CSI data, train pose estimation models, and manage .rvf files
+Record CSI data, train pose estimation models, and manage .rvf files