feat: 新增人员徘徊/静止行为分析功能

本次提交实现了完整的人员行为分析系统，包括：
1. 新增基于位置和跟踪ID的两种行为检测算法
2. 新增徘徊检测服务与行为处理器模块
3. 前后端集成算法配置界面与告警展示
4. 支持图片和视频流场景下的行为分析
5. 新增算法配置接口与文档说明

具体改动：
- 新增loitering_detection模型目录与算法实现
- 新增AlgorithmConfig组件实现可视化配置
- 扩展图片/视频检测接口支持算法参数传递
- 新增行为告警推送与前端展示页面
- 优化检测服务，集成行为分析逻辑
- 移除冗余日志输出，完善代码注释

models/loitering_detection/algorithms/loitering_detector.py

@@ -0,0 +1,251 @@
+"""
+基于跟踪ID的徘徊检测算法
+依赖跟踪ID，适用于跟踪稳定的场景
+"""
+
+import time
+from typing import Dict, List, Tuple, Optional
+from dataclasses import dataclass, field
+from collections import defaultdict
+
+
+@dataclass
+class PersonTrack:
+    """人员跟踪记录"""
+    person_id: int
+    first_seen: float
+    last_seen: float
+    positions: List[Tuple[int, int]] = field(default_factory=list)
+    last_position: Optional[Tuple[int, int]] = None
+    stationary_start: Optional[float] = None
+    total_duration: float = 0.0
+    stationary_duration: float = 0.0
+
+
+class LoiteringDetector:
+    """
+    徘徊检测器（基于跟踪ID）
+    
+    特点：
+    - 依赖跟踪 ID，需要稳定的跟踪器
+    - 可以检测长时间停留（徘徊）
+    - 可以检测静止不动（静止）
+    """
+    
+    def __init__(
+        self,
+        loitering_threshold: float = 300.0,  # 徘徊阈值（秒），默认5分钟
+        stationary_threshold: float = 2.0,    # 静止阈值（秒）
+        movement_threshold: float = 5.0,      # 移动阈值（像素）
+        cleanup_interval: float = 10.0        # 清理间隔（秒）
+    ):
+        self.loitering_threshold = loitering_threshold
+        self.stationary_threshold = stationary_threshold
+        self.movement_threshold = movement_threshold
+        self.cleanup_interval = cleanup_interval
+        
+        # 跟踪记录: {person_id: PersonTrack}
+        self._tracks: Dict[int, PersonTrack] = {}
+        self._last_cleanup = time.time()
+    
+    def _cleanup_old_tracks(self, max_age: float = 60.0) -> int:
+        """清理长时间未更新的跟踪记录"""
+        current_time = time.time()
+        to_remove = [
+            pid for pid, track in self._tracks.items()
+            if current_time - track.last_seen > max_age
+        ]
+        
+        for pid in to_remove:
+            del self._tracks[pid]
+        
+        return len(to_remove)
+    
+    def update(
+        self,
+        person_id: int,
+        position: Tuple[int, int]
+    ) -> Tuple[bool, float, bool, float]:
+        """
+        更新人员位置
+        
+        Args:
+            person_id: 人员ID
+            position: (x, y) 中心点坐标
+        
+        Returns:
+            is_loitering: 是否徘徊超过阈值
+            loitering_duration: 徘徊时长（秒）
+            is_stationary: 是否静止超过阈值
+            stationary_duration: 静止时长（秒）
+        """
+        current_time = time.time()
+        
+        # 定期清理
+        if current_time - self._last_cleanup > self.cleanup_interval:
+            self._cleanup_old_tracks()
+            self._last_cleanup = current_time
+        
+        # 获取或创建跟踪记录
+        if person_id not in self._tracks:
+            self._tracks[person_id] = PersonTrack(
+                person_id=person_id,
+                first_seen=current_time,
+                last_seen=current_time,
+                last_position=position
+            )
+            return False, 0.0, False, 0.0
+        
+        track = self._tracks[person_id]
+        track.last_seen = current_time
+        track.positions.append(position)
+        
+        # 计算总停留时长
+        track.total_duration = current_time - track.first_seen
+        
+        # 检查是否移动
+        is_moving = False
+        if track.last_position is not None:
+            distance = ((position[0] - track.last_position[0]) ** 2 + 
+                       (position[1] - track.last_position[1]) ** 2) ** 0.5
+            is_moving = distance > self.movement_threshold
+        
+        track.last_position = position
+        
+        # 更新静止状态
+        if is_moving:
+            # 如果移动了，重置静止计时
+            track.stationary_start = None
+            track.stationary_duration = 0.0
+        else:
+            # 如果没移动，更新静止时长
+            if track.stationary_start is None:
+                track.stationary_start = current_time
+            track.stationary_duration = current_time - track.stationary_start
+        
+        # 判断是否徘徊/静止
+        is_loitering = track.total_duration > self.loitering_threshold
+        is_stationary = track.stationary_duration > self.stationary_threshold
+        
+        return (
+            is_loitering,
+            track.total_duration,
+            is_stationary,
+            track.stationary_duration
+        )
+    
+    def detect(
+        self,
+        detections: List[Dict],
+        id_key: str = 'track_id'
+    ) -> List[Dict]:
+        """
+        批量检测徘徊状态
+        
+        Args:
+            detections: 检测结果列表，每项包含 'bbox' 和 track_id
+            id_key: 跟踪ID的字段名
+        
+        Returns:
+            添加 'loitering_info' 字段的检测结果
+        """
+        results = []
+        
+        for det in detections:
+            person_id = det.get(id_key)
+            if person_id is None:
+                results.append(det)
+                continue
+            
+            x1, y1, x2, y2 = det['bbox']
+            center = ((x1 + x2) // 2, (y1 + y2) // 2)
+            
+            is_loitering, loitering_duration, is_stationary, stationary_duration = \
+                self.update(person_id, center)
+            
+            det_copy = det.copy()
+            det_copy['loitering_info'] = {
+                'person_id': person_id,
+                'is_loitering': is_loitering,
+                'loitering_duration': round(loitering_duration, 2),
+                'is_stationary': is_stationary,
+                'stationary_duration': round(stationary_duration, 2),
+                'loitering_threshold': self.loitering_threshold,
+                'stationary_threshold': self.stationary_threshold
+            }
+            results.append(det_copy)
+        
+        return results
+    
+    def get_all_loitering(
+        self,
+        threshold: Optional[float] = None
+    ) -> List[Dict]:
+        """
+        获取所有徘徊超过阈值的人员
+        
+        Args:
+            threshold: 徘徊阈值（秒），默认使用初始化时的阈值
+        
+        Returns:
+            list: [{person_id, duration, positions}, ...]
+        """
+        threshold = threshold or self.loitering_threshold
+        
+        result = []
+        for person_id, track in self._tracks.items():
+            if track.total_duration > threshold:
+                result.append({
+                    'person_id': person_id,
+                    'duration': track.total_duration,
+                    'positions': track.positions.copy(),
+                    'is_stationary': track.stationary_duration > self.stationary_threshold,
+                    'stationary_duration': track.stationary_duration
+                })
+        
+        # 按时长排序
+        result.sort(key=lambda x: x['duration'], reverse=True)
+        return result
+    
+    def get_all_stationary(
+        self,
+        threshold: Optional[float] = None
+    ) -> List[Dict]:
+        """
+        获取所有静止超过阈值的人员
+        
+        Args:
+            threshold: 静止阈值（秒），默认使用初始化时的阈值
+        
+        Returns:
+            list: [{person_id, duration, position}, ...]
+        """
+        threshold = threshold or self.stationary_threshold
+        
+        result = []
+        for person_id, track in self._tracks.items():
+            if track.stationary_duration > threshold:
+                result.append({
+                    'person_id': person_id,
+                    'duration': track.stationary_duration,
+                    'position': track.last_position,
+                    'total_duration': track.total_duration
+                })
+        
+        result.sort(key=lambda x: x['duration'], reverse=True)
+        return result
+    
+    def reset(self):
+        """重置所有跟踪数据"""
+        self._tracks.clear()
+        self._last_cleanup = time.time()
+    
+    def get_stats(self) -> Dict:
+        """获取统计信息"""
+        return {
+            'total_tracks': len(self._tracks),
+            'loitering_count': len(self.get_all_loitering()),
+            'stationary_count': len(self.get_all_stationary()),
+            'loitering_threshold': self.loitering_threshold,
+            'stationary_threshold': self.stationary_threshold
+        }