Adobe, Inc.

Dalian University of Technology

Lu Zhang

Zhe Lin

Jianming Zhang

Radomir Mech

Kun Wang

Kai Liu

Shaopeng Zhong

Radomir Meeh

Haimin Jun

Yanquan Zou

Quanzhi Wang

Tianli Tang

Systems and methods provide editing operations in a smart editing system that may generate a focal point within a mask of an object for each frame of a video segment and perform editing effects on the frames of the video segment to quickly provide users with natural video editing effects. An eye-gaze network may produce a hotspot map of predicted focal points in a video frame. These predicted focal points may then be used by a gaze-to-mask network to determine objects in the image and generate an object mask for each of the detected objects. This process may then be repeated to effectively track the trajectory of objects and object focal points in videos. Based on the determined trajectory of an object in a video clip and editing parameters, the editing engine may produce editing effects relative to an object for the video clip.

System for automatic object mask and hotspot tracking

Systems and methods provide reframing operations in a smart editing system that may generate a focal point within a mask of an object for each frame of a video segment and perform editing effects on the frames of the video segment to quickly provide users with natural video editing effects. A reframing engine may processes video clips using a segmentation and hotspot module to determine a salient region of an object, generate a mask of the object, and track the trajectory of an object in the video clips. The reframing engine may then receive reframing parameters from a crop suggestion module and a user interface. Based on the determined trajectory of an object in a video clip and reframing parameters, the reframing engine may use reframing logic to produce temporally consistent reframing effects relative to an object for the video clip.

System for automatic video reframing

The present invention relates to a method for estimating distribution of urban road travel time in considering operation state of taxi, and belongs to the technical field of urban transportation planning and management. The distributions of path travel time are respectively estimated according to different operation states of the taxi. When the distribution of the path travel time is estimated, adjacent road sections in the road network are not independent. In the present invention, the Markov model is added to describe the correlation of the travel time distribution between the adjacent road sections, so as to increase science and accuracy of the estimation result. In the present invention, the weight is set according to the proportion of the number of the vehicles under two different operation states to obtain the final distribution of the path travel time. Driving behaviors of taxi drivers under two operation states of no passenger and passenger service may be different, so a difference between the travel time estimated from direct use of taxi data and a true value inevitably exists. The proposed model is calculated through Shenzhen data, which shows that the calculated travel time distribution function is more accurate after considering the operation states.

Method for estimating distribution of urban road travel time in considering operation state of taxi

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Dalian, China

Lu Zhang