Combatting fraud on travel, identity and breeder documents

It is important to combat fraud on travel documents (e.g., passports), identity documents (e.g., ID-card) and breeder documents (e.g., birth certificates) to facilitate the travel of bona-fide travelers and to prevent criminal cross-border activities, such as terrorism, illegal migration, smuggling, and human trafficking. However, it is...

Federated tool for anonymization and annotation in image data

The increasing complexity of security challenges requires Law Enforcement Agencies (LEAs) to have improved analysis capabilities, e.g., with the use of Artificial Intelligence (AI). However, it is challenging to make large enough high-quality training and testing datasets available to the community that is developing AI tools to support LEAs in...

Authentication of travel and breeder documents

Authentication of travel documents (e.g., passports) and breeder documents (e.g., birth certificates) is important to facilitate legal movement of passengers and to prevent cross-border crime, such as terrorism, smuggling, illegal migration and human trafficking. However, it is time consuming and difficult to verify all security features, the...

Document anonymization for border guards and immigration services

The current capabilities and capacities of border guards and immigration services can be enhanced using technologies that automate the analysis of travel, identity and breeder documents in order to detect fraud. These technologies can be relevant for countering emerging threats in document and identity verification (e.g., forged documents,...

ECOMOS software structure and key features

ECOMOS is a multinational effort within the framework of an EDA Project Arrangement. Its aim is to provide a generally accepted and harmonized European computer model for computing nominal Target Acquisition (TA) ranges of optronic imagers operating in the Visible or thermal Infrared (IR). The project involves close co-operation of defense and...

Flexible human-definable automatic behavior analysis for suspicious activity detection in surveillance cameras to protect critical infrastructures

Surveillance systems are essential for the protection of military compounds and critical infrastructures. Automatic recognition of suspicious activities can augment human operators to find relevant threats. Common solutions for behavior analysis or action recognition require large amounts of training data. However, suspicious activities and...

Target acquisition modeling over the exact optical path: Extending the EOSTAR TDA with the TOD sensor performance model

The Electro-Optical Signal Transmission and Ranging (EOSTAR) model is an image-based Tactical Decision Aid (TDA) for thermal imaging systems (MWIR/LWIR) developed for a sea environment with an extensive atmosphere model. The Triangle Orientation Discrimination (TOD) Target Acquisition model calculates the sensor and signal processing effects on...

Long-term behavior understanding based on the expert-based combination of short-term observations in high-resolution CCTV

The bottleneck in situation awareness is no longer in the sensing domain but rather in the data interpretation domain, since the number of sensors is rapidly increasing and it is not affordable to increase human data-analysis capacity at the same rate. Automatic image analysis can assist a human analyst by alerting when an event of interest...

Measuring cues for stand-off deception detection based on full-body non-verbal features in body-worn cameras

Deception detection is valuable in the security domain to distinguish truth from lies. It is desirable in many security applications, such as suspect and witness interviews and airport passenger screening. Interviewers are constantly trying to assess the credibility of a statement, usually based on intuition without objective technical support....

Complex Threat Detection: Learning vs. Rules, using a Hierarchy of Features

Theft of cargo from a truck or attacks against the driver are threats hindering the day to day operations of trucking companies. In this work we consider a system, which is using surveillance cameras mounted on the truck to provide an early warning for such evolving threats. Low-level processing involves tracking people and calculating motion...

Instantaneous threat detection based on a semantic representation of activities, zones and trajectories

Threat detection is a challenging problem, because threats appear in many variations and differences to normal behaviour can be very subtle. In this paper, we consider threats on a parking lot, where theft of a truck’s cargo occurs. The theft takes place in very different forms, in the midst of many people who pose no threat. The threats range...

A search engine for retrieval and inspection of events with 48 human actions in realistic videos

The contribution of this paper is a search engine that recognizes and describes 48 human actions in realistic videos. The core algorithms have been published recently, from the early visual processing (Bouma, 2012), discriminative recognition (Burghouts, 2012) and textual description (Hankmann, 2012) of 48 human actions. We summarize the key...

Spatio-Temporal Saliency for Action Similarity

Human actions are spatio-temporal patterns. A popular representation is to describe the action by features at interest points. Because the interest point detection and feature description are generic processes, they are not tuned to discriminate one particular action from the other. In this paper we propose a saliency measure for each individual...

Improved Action Recognition by Combining Multiple 2D Views in the Bag-of-Words Model

Action recognition is a hard problem due to the many degrees of freedom of the human body and the movement of its limbs. This is especially hard when only one camera viewpoint is available and when actions involve subtle movements. For instance, when looked from the side, checking one’s watch may look very similar to crossing one’s arms. In this...

Recognition and localization of relevant human behavior in videos

Ground surveillance is normally performed by human assets, since it requires visual intelligence. However, especially for military operations, this can be dangerous and is very resource intensive. Therefore, unmanned autonomous visual-intelligence systems are desired. In this paper, we present an improved system that can recognize actions of a...

Action recognition by layout, selective sampling and soft-assignment

This paper describes the TNO action recognition system that was used to generate the results for our submission to the competition track of the THUMOS ’13 challenge at ICCV ’13. This system deploys only the STIP features that were provided on the website of the challenge. A bag-of-features model is extended with three novelties

TNO at TRECVID 2013: Multimedia Event Detection and Instance Search

We describe the TNO system and the evaluation results for TRECVID 2013 Multimedia Event Detection (MED) and instance search (INS) tasks. The MED system consists of a bag-of-word (BOW) approach with spatial tiling that uses low-level static and dynamic visual features, an audio feature and high-level concepts. Automatic speech recognition (ASR)...

Automatic Human Action Recognition in a Scene from Visual Inputs

Surveillance is normally performed by humans, since it requires visual intelligence. However, it can be dangerous, especially for military operations. Therefore, unmanned visual-intelligence systems are desired. In this paper, we present a novel system that can recognize human actions. Central to the system is a break-down of high-level...