Multimodal Video Analysis for Crowd Anomaly Detection Using Open Access Tourism Cameras

Dataset Description This repository contains a dataset of object detection and instance segmentation events recorded over a 34-day period, from September 19, 2023 to October 23, 2023. The dataset comprises 50,384 individual records, capturing temporal, spatial, and classification data for objects identified in a open access video broadcast from the town of Morella, Spain. Dataset Structure The repository contains a single file, detections.csv. detections.csv serves as the primary dataset file. It encapsulates granular detection events, where each record includes the temporal timestamp, categorical class ID, model confidence metric, and spatial geometry. Comprehensive details regarding these columns are provided in the section below. Dataset Codebook The detections.csv file contains 8 columns. Column Name Data Type Description time String Timestamp of the detection in YYYY-MM-DD HH:MM:SSformat. class_id Integer Integer representing the object category based on the COCO dataset. Detected classes include: Class 0 (person), Class 1 (bicycle), Class 2 (car), Class 3 (motorcycle), Class 5 (bus), and Class 7 (truck). confidence Float Model certainty score (0.0 - 1.0). xmin Float X-coordinate of the bounding box's top-left corner (pixels). ymin Float Y-coordinate of the bounding box's top-left corner (pixels). xmax Float X-coordinate of the bounding box's bottom-right corner (pixels). ymax Float Y-coordinate of the bounding box's bottom-right corner (pixels). segment_mask String Contains a stringified list of [x, y] pixel coordinates that form a closed polygon around the detected object.数据集说明 本仓库收录了2023年9月19日至2023年10月23日共计34天的目标检测与实例分割事件数据集。该数据集包含50384条独立记录，捕获了来自西班牙莫雷利亚镇公开视频流中识别出的目标的时序、空间与分类信息。 数据集结构 本仓库仅包含一个文件：detections.csv。 detections.csv 为核心数据集文件，封装了精细化的检测事件数据，每条记录均包含时序时间戳、分类类别ID、模型置信度指标与空间几何信息。下文将详细说明各列的具体信息。 数据集编码手册 detections.csv 文件共包含8个字段。 字段名 数据类型 字段说明 time 字符串(String) 检测事件的时间戳，格式为YYYY-MM-DD HH:MM:SS class_id 整数(Integer) 基于COCO(Common Objects in Context)数据集的目标类别编号。本次检测覆盖的类别包括：类别0（人物）、类别1（自行车）、类别2（汽车）、类别3（摩托车）、类别5（公共汽车）及类别7（卡车） confidence 浮点数(Float) 模型置信度评分，取值范围为0.0至1.0 xmin 浮点数(Float) 边界框左上角的X轴像素坐标 ymin 浮点数(Float) 边界框左上角的Y轴像素坐标 xmax 浮点数(Float) 边界框右下角的X轴像素坐标 ymax 浮点数(Float) 边界框右下角的Y轴像素坐标 segment_mask 字符串(String) 存储字符串化的[x, y]像素坐标列表，这些坐标围绕检测目标构成闭合多边形，即分割掩码