Baseline method1

方法： Check height of the foot

優(yōu)點(diǎn)：easy

缺點(diǎn)： easily fooled，if a character skids to a stop

Baseline mehtod 2

方法： Check speed of the foot

優(yōu)點(diǎn)：easy

缺點(diǎn)： unreliable  the markers have some speed even during foot plants.         marker data is noisy

Bindiganavale 98  Proceeding of the International Workshop on Modeling and Motion Capture Techniques for Virtual Environments

方法： detect zero-crossing in acceration space of the end effectors

優(yōu)點(diǎn)： work well for non-noisy data

缺點(diǎn)：  unreliable on motion capture data  not reliabel when working with noisy signals    require manualy tagged-objects to avoid checking for collison with all the objects in the scene

Liu and Popovic 2002  Siggraph

方法：detect frames in which the feet are stationary

優(yōu)點(diǎn)：work well for non-noisy data

缺點(diǎn)： unreliable on motion capture data, not automatic .This method is dedicated to keyframed animation and is not intended to be applied to motion capture as it does not consider noise in the data.

Kovar 2002  Symposium on Computer Animation

題目：Footskate cleanup for motion capture editing

方法：use specific thresholds on the position and velocity of the feet to detect them.

優(yōu)點(diǎn)：

缺點(diǎn)：not reliable for motion capture animation as derivatives tend to amplify nosie in signals

Lee 2002 Siggraph

題目：Interactive control of AVstars animated with human motion data

方法： consider body segments and objects in the environment relative velocity and position to decide whether a body segment is in contact with an object in the scene or not

優(yōu)點(diǎn)：

缺點(diǎn)：not reliable for motion capture animation as derivatives tend to amplify nosie in signals

S.Menareais    2004  Symposium on Computer Animation

題目： Synchronization for Dynamic blending of motions

方法：use specific thresholds on the position and velocity of the feet to detect them

優(yōu)點(diǎn)：

缺點(diǎn) not reliable for motion capture animation as derivatives tend to amplify nosie in signals

Ikemoto 06 Symposium on Interactive 3D Graphics

方法：use a classifier to detect when foot plants should occur.By labeling a small set of frames, a user trains a classifier to detect when the foot should be planted.The classifier then automatically labels the remainder of the frames.

優(yōu)點(diǎn)： semi-automatic(訓(xùn)練部分需要手動(dòng)參與),

缺點(diǎn)： This method is dedicated to footplants detection and would be difficult to generilized to any kind of effectors and /or constraints .Indeed ,detecting another type of constraints would require to build a new kind of teature vectors and to train the calssifier once more.

想法：這個(gè)方法沒(méi)看懂。。。說(shuō)實(shí)話。。（一下午都在搞這個(gè)。。出了配了個(gè)Emacs。。。）

1） 首先怎么把三維mark點(diǎn)的軌跡映射到二維上，而且都是對(duì)齊的？ 從root點(diǎn)來(lái)搞？（貌似root點(diǎn)的確可以搞）

2） 下面就剩一些細(xì)節(jié)的東西。。21幀的問(wèn)題。。。

貌似的確是SKELETON相關(guān)的。。所以不適合我們的問(wèn)題。。。summer說(shuō)的的確是不錯(cuò)的。。

Le 06 Symposium on Computer Animation

題目：Robust kinematic constraint detection for motion data

方法：

優(yōu)點(diǎn)：

缺點(diǎn)：

這個(gè)Roubust Kinematic 看得我真是頭大的很啊。。。SVD分解，線性代數(shù)。。。映射空間。。。高斯噪聲。。。噪聲模板。。。我勒個(gè)去。。先補(bǔ)基礎(chǔ)。。