Automated equine behaviour monitoring

精明的看护人和兽医在很大程度上依赖于评估异常行为或变化 行为是身体疼痛或疾病的第一个迹象。刻板印象是重复的，高度程式化的， 无功能的运动反应和序列，马可以发展和可以表明异常行为， 行为不端或应对机制。专家（如看护人或兽医）将确定刻板印象， 管理条件后可能的疾病症状（即，住房、社会、锻炼、营养）和遗传 已经考虑过了。 运动马容易出现几种潜在的严重疾病，从腿部受伤到绞痛，可能导致突然的 如果症状出现后不立即治疗，则会死亡。 目前，亲自或通过网络摄像头观看赛马是唯一的行为监测解决方案 available. 当遵守持续监测时，这是有效的，但这不是可持续的和不寻常的行为 很多时候都没有被发现。自动监测技术将有助于克服这些限制。 这个项目将研究使用计算机视觉技术来自动标记不寻常的过程 马的行为，并将视频序列发送给马的主人，兽医或管理员。例如，绞痛 在马中与腹痛有关，当马咬它的两侧时， 比正常情况下躺下的时间更长，不断地将体重转移到后肢，爪子上，或者有一个描述的 食欲不振或根本不吃东西。严重的腹痛包括大量出汗，连续滚动， 持续的运动和剧烈的上下运动。计算机视觉技术将被探索 包括特征跟踪、光流以及骨骼动作识别技术。咨询项目预期 这个项目的一个重要部分是评估什么样的行为可以用什么样的技术和以什么样的准确度来检测。

The astute caretaker and the veterinarian heavily rely on the assessing unusual behaviour or a change in behaviour as the first sign of physical pain or disease. Stereotypies are repetitive, highly stylized, seemingly functionless motor responses and sequences that horses can develop and can signifiy abnormal behaviour, misbehaviour or coping mechanism. The experts (such as the caretaker or vet) will identify stereotypies as possible disease symptoms after management conditions (i.e., housing, social, exercise, nutrition) and genetic predisposition are already considered. Sport horses are prone to several potentially serious ailments from leg injuries to colic that can lead to sudden death if not treated shortly after symptoms occur. Currently, watching sport horses in person, or by web cam, are the only behaviour monitoring solutions available. This is effective when constant monitoring is complied to but this is not sustainable and unusual behaviours many times go undetected. An automatic monitoring technique would help in overcoming these limitations. This project will investigate using computer vision techniques to automate the process of flagging unusual behaviour in the horse and sending the video sequence to the horse owner, vet or caretaker. For example, colic in horses is associated with abdominal pain and abdominal pain is exhibited when the horse bites at his sides, lays down for longer than normal, continually shifts his weight on the hind limbs, paws or has a described appetite or does not eat at all. Severe abdominal pain includes signs of profuse sweating, continuous rolling, persistent movement and getting up and down violently. Computer vision techniques that will be explored include feature tracking, optical flow as well as skeletal action recognition techniques. The anticipated result of this project is an assessment of what behaviours can be detected with what techniques and at what accuracy.