Person detection and tracking techniques may be used to estimate pedestrian traffic in locations equipped with cameras. Persons detected in video data from the cameras may help determine existing pedestrian traffic data. Future pedestrian traffic estimation may be performed to estimate pedestrian traffic characteristics (such as volume, direction, etc.) Such traffic estimation may be provided to users for route planning/congestion information. A traffic map can be derived based on the number of people at or expected to be at certain locations. The map may be provided to users to provide traffic data and/or estimations.

Image and video based pedestrian traffic estimation

A computer implemented method for incorporating a representation of a participant into a virtual 3D environment substantially in real-time is provided. An image including a participant is captured by a camera. A contour of the participant is automatically determined. Depth data is automatically associated with the participant contour. A first virtual 3D representation of the participant is automatically generated by extruding the participant contour based on the associated depth data. An interaction between the first virtual 3D representation of the participant and a second virtual 3D representation of a second object is displayed.

Systems and methods for simulating three-dimensional virtual interactions from two-dimensional camera images

Embodiments of the present invention relate to automated methods and systems for analysing crowd congestion in a physical space. Video images are used to define a region of interest (205) in the space and partition the region of interest into an irregular array of sub-regions (220), to each of which is assigned a congestion contributor. Then, first and second spatial-temporal visual features are determined, and metrics are computed (225), (245), to characterise a degree of dynamic or static congestion in each sub-region. The metrics and congestion contributors are used to generate (260) an indication of the overall measure of congestion within the region of interest.

Crowd congestion analysis

A method for automatically detecting and tracking objects in a scene. The method acquires video frames from a video camera; extracts discriminative features from the video frames; detects changes in the extracted features using background subtraction to produce a change map; uses the change map to use a hypothesis to estimate of an approximate number of people along with uncertainty in user specified locations; and using the estimate, track people and update the hypotheses for a refinement of the estimation of people count and location.

Method for automatic detection and tracking of multiple objects

A motion detection method, apparatus and system are disclosed in the present invention, which relates to the video image processing field. The present invention can effectively overcome the influence of the background on motion detection and the problem of object “conglutination” to avoid false detection, thereby accomplishing object detection in complex scenes with a high precision. The motion detection method disclosed in embodiments of the present invention comprises: acquiring detection information of the background scene and detection information of the current scene, wherein the current scene is a scene comprising an object(s) to be detected and the same background scene; and calculating the object(s) to be detected according to the detection information of the background scene and the detection information of the current scene. The present invention is applicable to any scenes where moving objects need to be detected, e.g., automatic passenger flow statistical systems in railway, metro and bus sectors, and is particularly applicable to detection and calibration of objects in places where brightness varies greatly.

Motion detection method, apparatus and system

A system and method for automated and/or semi-automated analysis of video for discerning patterns of interest in video streams. In a preferred embodiment, the present invention is directed to identifying patterns of interest in indoor settings. In one aspect, the present invention deals with the change detection problem using a Markov Random Field approach where information from different sources are naturally combined with additional constraints to provide the final detection map. A slight modification is made of the regularity term within the MRF model that accounts for real-discontinuities in the observed data. The defined objective function is implemented in a multi-scale framework that decreases the computational cost and the risk of convergence to local minima. To achieve real-time performance, fast deterministic relaxation algorithms are used to perform the minimization. The crowdedness measure used is a geometric measure of occupancy that is quasi-invariant to objects translating on the platform.

Bjoern Stenger

Papers

Real-time crowd density estimation from video