一是建立了一种模型 general energy map , 代表行人会走到这个地方的难易程度， 或者说一个行人会出现在场景中一个位置的概率。
通过场景中的K个观察点（observation of ）建立似然函数使用梯度下降法更新参数
静态人群的检测方法来源于参考文章 ,笔记最后detecte stationary crowd group region的链接即是。
路径生成的方法主要来源于参考的两篇文章标号[17, 32]，在笔记最后generate pedestrian walking path的两篇链接即是。
第二个创新点是建立了一个新的pedestrian walking path dataset，在一个video中标注了约12000人行为信息。
A novel model is proposed form pedestrian behavior modeling by including stationary crowd groups as a key component.
Through inference based on the interactions between stationary crowd groups and pedestrians, our model can be used to investigate pedestrian behaviors.
A large pedestrian walking path dataset is built.
The walking routes of more than 12, 000 pedestrians from a one-hour crowd video are annotated.
The effectiveness of the proposed model is demonstrated by multiple applications on the proposed dataset. Including
compare with existing agent based models, three points :
A pedestrian usually selects the most convenient and effcient path for reaching the destination ;
propose a general scene energy map to model the traveling diffculty of enery location of the scene .
is also a probability map shows the probability of pedestrian appearing at each location.
Personalized energy maps are generated based on the general energy map and a personality parameter P;
can be view as a different pedestrians' interpretations of the general map .
is modeled with three channel caculated based on
- : Scene Layout
- : Moving Pedestrians
- : Stationary Groups
are weight paramters for different terms
- : a set of locations occuied by scene obstacles which are unreachables
measures the distance from the current location to its nearest scene obstacle location
- : a parameter indicating the influence bandwidth(importance).
- : the th moving pedestrian
- : the spatical location of at current time
measures the distance from the current location to the moving pedestrian
- : the influence bandwidth of the moving pedestrian term.
- : the th stationary crowd group region automatically dected
measures the distance from to the stationary crowd group region
- : the influence bandwidth of the stationary crowd group term
- : calculated as the average distance among group members
measure the sparsity of stationary crowd group region
- : control the influence of group sparsity on estimation result
: personality parameter, equivalent to the influence bandwidth of the terms
- large means the energy values are small at locations near obstacles and stationary crowd group.
- small means that the pedestrian is walking aggressively and cares less about abstacles
: the most effcient and probable route from to according to the current energy map or
by dividing a marginalization term, , the energy map can be transformed to a probility distribution :
Gaven as independent observation of , the likelihood of these observation is :
Parameter can be then be optimized as
Gradient descent is used for updating parameters
The strong correlations between (a) and (b)-(c) indicate that stationary crowd is a key factor that decreases traffic effcienty.
A pedestrian is not sensitive to scene obstacles
Apedestrian might prefer to adjust walking speed rather than change predecided walking direction to avoid close contact with other moving pedestrians.
When stationary crowds emerge in front of a pedestrian, he/she has to change his/her walking route to bypass the stationary crowds.
over cost value is define as
- : walking cost of the observed route based on the current map
- : the cost of the optimized route
- small indicates better match
conclusion : the influence of stationary crowd groups is necessary when modeling pedestrian behaviors, and the stationary crowd groups should be modeled differently from scene obstacles.
Gaven and part of the walking path, we can also predict the destination of this pedestrian
- : the first half of observated trajectory
- : the first half of which is the optimized route ended with
- : the distance between the two half trajectories
- Smaller indicates that the pedestrian is more likely to go to the destination which are manually labeled.
- : the observed trajectory of current pedestrian
- : the optimal walking path calculated using personalized energy
- : the distance between the two trajectories
All the pedestrians can be classified into three categories based on their walking behaviors: aggressive, conservative, and abnormal.
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detecte stationary crowd group region
S. Yi, X. Wang, C. Lu, and J. Jia L0 Regularized Stationary Time Estimation for Crowd Group Analysis
generate pedestrian walking path
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social force model
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