面向畜禽肉加工领域的畜类胴体多维度与多部位数据集

数据集内容：包括67组畜类胴体点云数据，主要用于进行畜类自动化智能分块点（前后段下刀点的位置）的检测，提供三维位置坐标信息。采集方案：首先，根据任务定位需求确定图像数据集的维度类别，采集胴体三维深度图；其次，使用双目结构光相机采集生产加工车间实际点云数据并对收集到的数据进行筛选（将采集到的未能包含完整猪胴体的数据剔除）；最后，通过相关算法统计猪胴体体长数据，为下一步体长分级提供先验信息。针对彩色图像数据，首先，确定图像数据集的标签和类别（前段分块点，后段分块点）

Dataset Content: Includes 67 sets of livestock carcass point cloud data, mainly used for detecting automated intelligent cutting points for livestock carcass segmentation (positions of front and rear segment cutting points), providing three-dimensional position coordinate information.

Collection Protocol: First, determine the dimensional categories of the image dataset based on task positioning requirements, and collect three-dimensional depth maps of the carcasses; second, use a binocular structured light camera to collect actual point cloud data from the production and processing workshop, and screen the collected data by removing the data that fails to include complete pig carcasses; finally, statistically calculate the body length data of pig carcasses via relevant algorithms to provide prior information for subsequent body length grading.

For color image data: First, determine the labels and categories of the image dataset (front segment cutting point, rear segment cutting point).

搜集汇总

背景与挑战

背景概述

该数据集包含67组畜类胴体点云数据，旨在支持畜禽肉加工领域的智能分块点检测，提供三维位置坐标信息。数据通过双目结构光相机采集三维深度图，并经过筛选和处理，用于统计猪胴体体长，为自动化分割和分级提供基础。