Method and apparatus for generating predictive models

A technology for predicting models and predicting images, used in character and pattern recognition, instrumentation, computing, etc., and can solve problems such as deep models for crowd counting that have not yet been developed

Active Publication Date: 2018-01-23
BEIJING SENSETIME TECH DEV CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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  • Method and apparatus for generating predictive models
  • Method and apparatus for generating predictive models
  • Method and apparatus for generating predictive models

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Embodiment Construction

[0038]Reference will now be made in detail to certain specific embodiments of the invention, including the best mode contemplated by the inventors for carrying out the invention. Examples of these specific embodiments are illustrated in the accompanying drawings. While the invention has been described in conjunction with these particular embodiments, it is to be understood that the invention is not limited to the described embodiments. On the contrary, it is intended to cover all alternatives, modifications and equivalents as may be included within the spirit and scope of the invention as defined by the appended claims. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. The present invention may be practiced without some or all of these specific details. In other instances, well known process operations have not been described in detail in order to unnecessarily obscure the present inve...

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Abstract

Disclosed is method for generating a predictive model to predict a crowd density distribution and counts of persons in image frames, comprising: training a CNN by inputting one or more crowd patches from frames in a training set, each of the crowd patches having a predetermined ground-truth density distribution and counts of persons in the inputted crowd patches; sampling frames from a target scene image set and receiving the training images from the training set that having the determined ground-truth density distribution and counts/number, retrieving similar image data from the received training frames for each of the sampled target image frames to overcome scene gaps between the target scene image set and the training images; and fine-tuning the CNN by inputting the similar image data to the CNN so as to determine a predictive model for predicting the crowd density map and counts of persons in image frames.

Description

technical field [0001] The present application relates to devices and methods for generating predictive models to predict crowd density distribution and people counts in image frames. Background technique [0002] Counting crowds of pedestrians in video has a strong demand in video surveillance and thus has attracted a lot of attention. Crowd counting is a challenging task due to heavy occlusions, scene perspective distortions, and diverse crowd distributions. Due to the difficulty of pedestrian detection and tracking in crowd scenarios, most state-of-the-art methods are regression-based and aim to learn the mapping between low-level features and crowd counts. However, these works are scene-specific, i.e., a crowd counting model learned for a specific scene can only be applied to the same scene. Taking into account unseen scenes or changed scene layouts, the model must be retrained with new annotations. [0003] There have been many works to count pedestrians by detection...

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Application Information

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IPC IPC(8): G06K9/66
CPCG06V20/53G06V10/454G06V30/194
Inventor 王晓刚张聪李鸿升
Owner BEIJING SENSETIME TECH DEV CO LTD
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