Everseen Limited

Vasile Gui

Dan Pescaru

Alan O'Herlihy

Bogdan Ciubotaru

Cosmin Cernazanu-Glavan

Ovidiu Parvu

Ciprian Petru David

Joe Allen

Mark Ibbotson

Raymond Hegarty

Dan Alin Crisfalusi

Margaret Hartnett

Alan O'herlihy

Cosmin Cernazanu

Arion Alexandru

Cristina Todoran

A method and apparatus for the identification of suspect behaviour in a retail environment, the method comprising: detecting a person in a frame of said stream of video data; extracting a set of activities of the identified person from the stream of video data; assigning a numeric value to each extracted activity in the set of extracted activities, said numeric value representative of a threat level of the activity; accumulating said numeric values to provide a behaviour score; and identifying a behaviour as being suspect when the behaviour score reaches a target threshold value associated with the behaviour.

Method and apparatus for the detection of behaviours in a retail environment

A system for process shaping in a retail store environment comprises a video generation and processing component, a data source integration and aggregation component for aggregating and integrate information received from various sources, a process sensing component for generating one or more continuous processes, a process aggregator and weighing component for aggregating the one or more continuous processes into a merged weighted process, a proof of problem and value component for determining one or more process variations, a ripple effect analyser for sending one or more nudging messages to the retail store environment, and a gamified feedback algorithm component for communicating a nudging action corresponding to a nudging message, to one or more entities in the retail store environment.

System and method for process shaping

An enhanced service system comprises a pair of first wires between a first position proximal to an entry point of a drive through facility and a second position proximal to a receiving window in the drive through facility, and an aerial host unit coupled to the pair of first wires using a pair of first and second host wires. The aerial host unit is longitudinally movable between the first position and the second position and includes an aerial host member moveably supported by the first and second host wires to move laterally between the pair of first wires to approach an incoming customer vehicle, facilitate the customer to place an order, receive payment from the customer, and direct the customer to the receiving window where the aerial host member retrieves the items corresponding to the placed order from the receiving window and transfers the retrieved items to the customer.

Enhanced service system for a drive through facility

A system for recognizing human activity from a video stream includes a classifier for classifying an image frame of the video steam in one or more classes and generating a class probability vector for the image frame based on the classification. The system further includes a data filtering and binarization module for filtering and binarizing each probability value of the class probability vector based on a pre-defined probability threshold value. The system furthermore includes a compressed word composition module for determining one or more transitions of one or more classes in consecutive image frames of the video stream and generating a sequence of compressed words based on the determined one or more transitions. The system furthermore includes a sequence dependent classifier for extracting one or more user actions by analyzing the sequence of compressed words to and recognizing human activity therefrom.

Quantized transition change detection for activity recognition

A method for segmenting motion data and inferring layering order in a video includes segmenting a first image frame of the video using intra-frame mode estimation, segmenting further image frames of the video using inter-frame mode matching, generating a label change map for a current segmented image frame by generating a binary map of the current segmented image frame, and then marking one or more pixels whose labels have changed with respect to a previous segmented image frame, detecting one or more non-still image segments of the current segmented image frame, detecting one or more moving image segments in the one or more non-still image segments, estimating motion of the one or more moving image segments, representing each moving segment as a vector of seven parameters, and clustering one or more similar moving segment vectors based on corresponding one or more parameters.

Layered motion representation and extraction in monocular still camera videos

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Timis, Romania

Vasile Gui