In this paper, we focus on the challenging problem of estimating landmark points, such as the rat's eyes and joints, only with image processing and quantify the motion behavior of the rat. Quantifying rat behavior through video surveillance is crucial for medicine, neuroscience, and other fields. As the first large and standardized mouse pose dataset, our proposed mouse pose dataset will help advance research on animal pose estimations and assist in application areas related to animal experiments. We employed modified object detections and pose estimation algorithms to achieve precise, effective, and robust performances. ![]() It is another important link to establish a benchmark model for 2D mouse pose estimations. Then, we created simple, yet effective software that works for annotating images. Moreover, to improve the annotation efficiency, five keypoints of mice are creatively proposed, in which one keypoint is at the center and the other two pairs of keypoints are symmetric. All the images were captured from interacting lab mice through a stable single viewpoint, including 5 distinct species and 20 mice in total. Our mouse pose dataset contains 40,000 frames of RGB images and large-scale 2D ground-truth motion images. Here, we resolve this difficulty by introducing the mouse pose dataset. One of the most prominent problems is the lack of uniform and standardized training datasets. Although methods for mouse pose estimations have developed, bottlenecks still exist. Accurate and efficient mouse pose estimations using computer vision are necessary. Mouse pose estimations have important applications in the fields of animal behavior research, biomedicine, and animal conservation studies. ![]() © 2018, The Author(s), under exclusive licence to Springer Nature America, Inc. Finally, we extended the method to more challenging imaging situations and videos of freely moving mice. We recapitulated reported findings on insect gait dynamics and demonstrated LEAP’s applicability for unsupervised behavioral classification. We validated LEAP using videos of freely behaving fruit flies and tracked 32 distinct points to describe the pose of the head, body, wings and legs, with an error rate of <3% of body length. LEAP offers fast prediction on new data, and training with as few as 100 frames results in 95% of peak performance. This framework consists of a graphical interface for labeling of body parts and training the network. Here we introduce LEAP (LEAP estimates animal pose), a deep-learning-based method for predicting the positions of animal body parts. Either that, or I'll put it on a friend's machine, set the dimming level to all black, give it a relatively large "light circle," and then assign it to his brightness key :).The need for automated and efficient systems for tracking full animal pose has increased with the complexity of behavioral data and analyses. I intend to put this to use during my next OS X presentations, as I think it will help folks follow along with the cursor movements. Also, although Mouseposé is free, it does require you to register on Boinx's site to get a serial number - name and email address are required, and you can opt out of their update mailings. ![]() I would much rather use something easier to reach on the keyboard and not give up a function key to the activation keystroke. On the downside, the hot keys available are only the standard function keys you can't add a modifier, nor can you assign any other key combo. You can also specify (somewhat) the hot key to be used to activate Mouseposé, and have it automatically deactivate after a specified interval of time instead of remaining active. You can modify the size of the circle, the amount of dimming applied, and even the color of the dimming - turn your screen a dark shade of red, for instance, while Mouseposé is active. Mouseposé runs as an application, so there's no "low level" compatibility issue to worry about (it's been very stable during my time using it). Once activated, you can continue to use your Mac as you normally would, and Mouseposé won't deactivate until you press its hotkey again. ![]() You activate it via a hotkey, and it then dims the screen and leaves an undimmed circle around the mouse, making it very easy to see the cursor's location. As you can see in the screenshot at left, Mouseposé is somewhat like Exposé for your mouse pointer. It's also useful, though, in a text editing document when you've lost sight of the I-beam cursor. It will be of particular interest to presenters and those who demonstrate OS X software in large rooms.
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