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DoW: pp. 42-44 WP1: Intelligent Monitoring and Automatic Detection of Threats.

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Presentation on theme: "DoW: pp. 42-44 WP1: Intelligent Monitoring and Automatic Detection of Threats."— Presentation transcript:

1 DoW: pp WP1: Intelligent Monitoring and Automatic Detection of Threats

2 Outline Introduction Tasks Deliverables Milestones Discussion on Participants roles and resource allocation Participants Roles GUT suggestions for the tasks WP1 work organization: Conference calls, editorial tasks, reviewers, etc. Identify partners collaborating in the other WPs close to WP1 Outline the content of the deliverables at least for the first one 10:30-11:30 WP1 Session pt.1 11:30-12:00 Coffee Break 12:00-13:30 WP1 Session pt. 2, contd. if necessary 13:30-15:00 Lunch

3 Introduction

4 Task: 1 1. Establishing the framework of the System for secure data gathering and transmission including: 1.1. Building a prototype of the Node Station (NS), which will be installed in various points of city agglomerations and tested in fields conditions - GUT 1.2. Central Station (CS) construction - GUT 1.3. Developing a methodology for generating scene descriptions utilizing processed audio and video signals, in conjunction with data acquired from the NSs (biometric sensors, cell phones identification, transmission scanners, monitoring devices, GPS, micro- transmitters, RFID tags) – PSI, GUT 1.4. Real-time secure data transmission to the CS and then to police mobile terminals – Apertus, Moviquity, TUKE

5 Task: 2 2. Analyzing, defining and integrating new and current technologies used for image, video and voice recognition and extraction, especially for: 2.1. Defining and recognizing particular audio signals (calling for help in European languages, shooting, etc.) – PSI, TUKE, GUT 2.2. Creating algorithms for acquisition and pre- processing of audio and image signals – PSI, TUKE, INNOTEC, GUT 2.3. Implementing methods for extracting human biometric features from images - GUT, PUT 2.4. Implementing image analysis, motion tracking and object detection – FHTW, GUT

6 Deliverables D1.1 Report on the collection and analysis of user requirements (M10) D1.2 Report on NS and CS hardware construction (M20) D1.3 Document reporting on acquired results of pilot trial (M45) D1.4 Multimedia database documentation with analysis of recommended algorithms (M45) D1.5 Specification of procedures for data exchange including definition of system usage with respect to the law and police regulations (M50) D1.6 Dissemination report (M60) D1.7 Complete documentation and manuals for all classes of users of the system (M60) D1.8 The final version of the monitoring system with validation report of recommendation and guidelines (M60)

7 Milestones M1.1: Completed detailed specifications for the system (M15) M1.2: Intermediary report for D1.2: (M18). M1.3: Working Node Station hardware with basic user interface (M20) M1.4: Working Central Station hardware with basic user interface (M20) M1.5: Intermediary report for D1.6: Scene description algorithms (M30) M1.6: Algorithms for automatic detection of abnormal behaviour based on audio, video and other signals (M35) M1.7: The methodology and model for data gathering (M36) M1.8: End-user Interface following the specification (M45) M1.9: Prototypes of Node Stations ready to be installed in selected agglomerations (M50) M1.10: Completed set of documentations and manuals, published scientific papers (M60)

8 WP1 Schedule M1.8 D1.3-4 M45 D1.1 M10 M1.1 M15 M1.2 M18 M1.3-4 D1.2 M20 M1.5 M30 M1.6 M35 M1.7 M35 M1.9 D1.5 M50 M1.10 D1.6,7,8 M60 user requ. specs intmed. report for HW NS CS w/ GUI hardware report scene descript. detection algor. data gathering results of pilot trial MMDB user GUI data exch. for police NS ready reports docs, manuals final verification T1.2 M25

9 Discussion on Participants roles and resource allocation

10

11 All partners explain their main contributions to WP1 per task per deliverable Check resource allocation according to DoW Preliminary objectives per task distribution Identify main tasks to be done inside each task o Define a detailed work ‐ plan for the next three months o Identify task responsible partner o WP1 work organisation: Conference calls, editorial tasks, reviewers, etc. Identify partners collaborating in the other WPs close to WP1 Outline the content of the deliverables at least for the first one

12 Partners’ contributions to WP1 All Partners should now explain their main contributions to WP 1 per task per deliverable

13 Initially declared Participant roles Participant 2Apertus- task: 1.4 Participant 20FHTW - task: 2.4 Participant 5GUT - task 1 and 2 Participant 6 INNOTEC - task: 2.2 Participant 8GHP - consulting and tool testing Participant 9MOVIQUITY - task 1.4 Participant 10PSI - task: 1.3, Participant 11PSNI - task: 5.2 – should it be 2.2? Participant 12 PUT - role not defined in DoW? Participant 18TUKE - task: 1.4,

14 2 Apertus - task: 1.4 Apertus Public Foundation for Open Training and Distance Learning founded by Hungarian Government, CEO, Péter Racskó head of the IT department, Zoltan Nagy Task 1.4 – Real-time secure data transmission to the CS and then to police mobile terminals Task 1Task 2 Navigate to: DsMs

15 2 Apertus - task: 1.4 Discuss Participant suggestions for the task / other tasks Specification of the system – M1.1 – M15 Report on transmission technologies, standards and protocols aimed at secure real-time transmission - Should be ready before D1.2 – M20 The report after implementation will be used in – Data exchange procedures - D1.5 – M50 Dissemination, Documentation, Manuals, Recommendations, Guidelines – D1.6  8 – M60 Task 1Task 2 Navigate to: DsMs

16 20 FHTW - task: 2.4 The University of Applied Sciences Technikum, Wien Prof. Dr.-Ing. Jakob Wassermann Task 2.4 – Implementing image analysis, motion tracking and object detection Task 1Task 2 Navigate to: DsMs

17 20 FHTW - task: 2.4 Task 1Task 2 Navigate to: DsMs Discuss Participant suggestions for the task / other tasks Specification of the system – M1.1 – M15 NS, CS basic user interfaces - Software released M1.3,4 – M20 Scene description algorithms – M1.5 – M30 Detection of abnormal behavior – M1.6 – M35 Multimedia database with algorithms - D1.4 – M45 image analysis, motion tracking, object detection – implementation on smart cameras End-user interfaces – M1.8 – M45 Dissemination, Documentation, Manuals, Recommendations, Guidelines – D1.6  8 – M60

18 6 InnoTec - task: 2.2 InnoTec DATA GmbH & Co. KG, Germany Nils Johanning Task 2.2 – Creating algorithms for acquisition and pre- processing of audio and image signals Task 1Task 2 Navigate to: DsMs

19 6 InnoTec - task: 2.2 Task 1Task 2 Navigate to: DsMs Discuss Participant suggestions for the task / other tasks Specification of the system – M1.1 – M15 Hardware construction - D1.2 – M20 Int.med. Report for HW – M1.2 – M18 Providing hardware for NS, CS, cameras with noise and vibrations reduction, microphone arrays, multi-channel sound cards, sensors, RFID modules (other tracking techniques) NS, CS basic user interfaces - Software released M1.3,4 – M20 Methodology and model for data gathering – M1.7 – M36 End-user interfaces – M1.8 – M45 NS, CS prototypes ready for installation – M1.9 – M50 Dissemination, Documentation, Manuals, Guidelines – D1.6  8 – M60

20 8 GHP – consulting and tool testing General Headquarters of Police, Poland Radosław Chinalski, Deputy Director of the Criminal Bureau Task: – Consulting and tool testing Task 1Task 2 Navigate to: DsMs

21 Task 1Task 2 Navigate to: DsMs 8 GHP – consulting and tool testing Discuss Participant suggestions for the task / other tasks User requirements - D1.1 - M10 Specification of the system – M1.1 – M15 NS, CS basic user interfaces - Software released M1.3,4 – M20 Pilot trials – D1.3 – M45 End-user interfaces – M1.8 – M45 Data exchange procedures - D1.5 – M50 Dissemination, Documentation, Manuals, Recommendations, Guidelines – D1.6  8 – M60

22 9 Moviquity – task 1.4 APIF MOVIQUITY SA, Spain José Manuel Gil, Managing Director Task 1.4 – Real-time secure data transmission to the CS and then to police mobile terminals Task 1Task 2 Navigate to: DsMs

23 9 Moviquity – task 1.4 Task 1Task 2 Navigate to: DsMs Discuss Participant suggestions for the task / other tasks Specification of the system – M1.1 – M15 Hardware construction D1.2 – M20 Int.med. Report for HW – M1.2 – M18 Software for PDAs Wireless engineering, network solutions Providing wireless network architecture NS, CS basic user interfaces - Software released M1.3,4 – M20 Methodology and model for data gathering – M1.7 – M36 End-user interfaces – M1.8 – M45 Data exchange procedures - D1.5 – M50 NS, CS prototypes ready for installation – M1.9 – M50 Dissemination, Documentation, Manuals, Recommendations, Guidelines – D1.6  8 – M60

24 10 PSI – task 1.3, 2.1, 2.2 Products and Systems of Information Technology, Germany Dr. Stephan Gottwald, Project Manager, Business Consultant Dr Ing Haluk Sarlan, Consultant, Project Manager Kambiz Fazel, Consultant, Software Engineer Task 1.3 – Developing a methodology for scene descriptions with audio and video signals in conjunction with data from NS Task 2.1 – Defining and recognizing particular audio signals Task 2.2 – Algorithms for acquisition and pre-processing of audio and video signals Task 1Task 2 Navigate to: DsMs

25 10 PSI – task 1.3, 2.1, 2.2 Task 1Task 2 Navigate to: DsMs Discuss Participant suggestions for the task / other tasks Specification of the system – M1.1 – M15 Hardware construction D1.2 – M20 Int.med. Report for HW – M1.2 – M18 Technology for control centers – PSIcommand, PSIecontrol NS, CS basic user interfaces - Software released M1.3,4 – M20 Methodology and model for data gathering – M1.7 – M36 End-user interfaces – M1.8 – M45 Data exchange procedures - D1.5 – M50 NS, CS prototypes ready for installation – M1.9 – M50 Dissemination, Documentation, Manuals, Recommendations, Guidelines – D1.6  8 – M60

26 11 PSNI – task 5.2 Police Service of Northern Ireland Gerald Murray Task 5.2? Task 1Task 2 Navigate to: DsMs

27 11 PSNI – task 5.2 Task 1Task 2 Navigate to: DsMs Discuss Participant suggestions for the task / other tasks User requirements - D1.1 - M10 Specification of the system – M1.1 – M15 NS, CS basic user interfaces - Software released M1.3,4 – M20 Methodology and model for data gathering – M1.7 – M36 Pilot trials – D1.3 – M45 End-user interfaces – M1.8 – M45 Data exchange procedures - D1.5 – M50 Dissemination, Documentation, Manuals, Recommendations, Guidelines – D1.6  8 – M60

28 12 PUT – role not defined Poznan University of Technology, Poland Prof. Adam Dabrowski Task 1Task 2 Navigate to: DsMs

29 12 PUT – role not defined Task 1Task 2 Navigate to: DsMs Discuss Participant suggestions for the task / other tasks Specification of the system – M1.1 – M15 NS, CS basic user interfaces - Software released M1.3,4 – M20 Scene description algorithms – M1.5 – M30 Detection of abnormal behavior – M1.6 – M35 End-user interfaces – M1.8 – M45 Multimedia database with algorithms - D1.4 – M45 Biometry HMI (human-machine interfaces) Dissemination, Documentation, Manuals, Recommendations, Guidelines – D1.6  8 – M60

30 18 TUKE – task 1.4, 2.1, 2.2 Technical University of Kosice, Slovakia Anton Cizmar, rector Prof. Lubomir Dobos Task 1.4 – Real-time secure data transmission to the CS and then to police mobile terminals Task 2.1 – Defining and recognizing particular audio signals Task 2.2 – Algorithms for acquisition and pre-processing of audio and video signals Task 1Task 2 Navigate to: DsMs

31 18 TUKE – task 1.4, 2.1, 2.2 Task 1Task 2 Navigate to: DsMs Discuss Participant suggestions for the task / other tasks Specification of the system – M1.1 – M15 NS, CS basic user interfaces - Software released M1.3,4 – M20 Scene description algorithms – M1.5 – M30 Detection of abnormal behavior – M1.6 – M35 End-user interfaces – M1.8 – M45 Multimedia database with algorithms - D1.4 – M45 Sound acquisition and processing Sound recognition Speech processing Sound transfer Dissemination, Documentation, Manuals, Recommendations, Guidelines – D1.6  8 – M60

32 5 GUT - task: 1 and 2 Gdansk University of Technology, Poland Prof. Andrzej Czyżewski Task 1 – Establishing the framework of the System for secure data gathering and transmission Task 2 – Analyzing, defining and integrating new and current technologies used for image, video and voice recognition and extraction Task 1Task 2 Navigate to: DsMs

33 5 GUT - task: 1 and 2 Task 1Task 2 Navigate to: DsMs Discuss Participant suggestions for the task / other tasks Go to Task 1 and 2 GUT suggestions

34 Resource allocation Participant 2Apertus- task: 1.4 Participant 20FHTW - task: 2.4 Participant 5GUT - task 1 and 2 Participant 6 INNOTEC - task: 2.2 Participant 8GHP - consulting and tool testing Participant 9MOVIQUITY - task 1.4 Participant 10PSI - task: 1.3, Participant 11PSNI - task: 5.2 – should it be 2.2? Participant 12 PUT - role not defined in DoW? Participant 18TUKE - task: 1.4,

35 Objectives and tasks

36 1 st Deliverable(s) Outline the content of the deliverables at least for the first one: D1.1 Report on the collection and analysis of user requirements (M10) D1.2 Report on NS and CS hardware construction (M20) Navigate to: All Deliverables List

37 Summary Define a detailed work-plan for the next three months WP 1 work organisation: Conference calls, editorial tasks, reviewers, etc. Task 1Task 2 Navigate to: DsMs

38 Relations with other partners Identify partners collaborating in the other WPs close to WP1 WP2 - Identification and Observation of Mobile Objects in Urban Environment PUT, MOVIQUITY, TUKE WP6 - Interactive Multimedia Applications Portal for Intelligent Observation System MOVIQUITY, PUT, TUKE WP7 - Biometrics and Intelligent Methods for Extraction and Supplying Security Information PSI, PUT, GUT

39 Task: 1 1. Establishing the framework of the System for secure data gathering and transmission including: 1.1. Building a prototype of the Node Station (NS), which will be installed in various points of city agglomerations and tested in fields conditions - GUT 1.2. Central Station (CS) construction - GUT 1.3. Developing a methodology for generating scene descriptions utilizing processed audio and video signals, in conjunction with data acquired from the NSs (biometric sensors, cell phones identification, transmission scanners, monitoring devices, GPS, micro- transmitters, RFID tags) – PSI, GUT 1.4. Real-time secure data transmission to the CS and then to police mobile terminals – Apertus, Moviquity, TUKE, GUT Back

40 Task: 2 2. Analyzing, defining and integrating new and current technologies used for image, video and voice recognition and extraction, especially for: 2.1. Defining and recognizing particular audio signals (calling for help in European languages, shooting, etc.) – PSI, TUKE, GUT 2.2. Creating algorithms for acquisition and pre- processing of audio and image signals – PSI, TUKE, INNOTEC, GUT 2.3. Implementing methods for extracting human biometric features from images - GUT, PUT 2.4. Implementing image analysis, motion tracking and object detection – FHTW, GUT Navigate: Back

41 Navigate: Back Deliverables D1.1 Report on the collection and analysis of user requirements (M10) D1.2 Report on NS and CS hardware construction (M20) D1.3 Document reporting on acquired results of pilot trial (M45) D1.4 Multimedia database documentation with analysis of recommended algorithms (M45) D1.5 Specification of procedures for data exchange including definition of system usage with respect to the law and police regulations (M50) D1.6 Dissemination report (M60) D1.7 Complete documentation and manuals for all classes of users of the system (M60) D1.8 The final version of the monitoring system with validation report of recommendation and guidelines (M60)

42 Navigate: Back Milestones M1.1: Completed detailed specifications for the system (M15) M1.2: Intermediary report for D1.2: (M18). M1.3: Working Node Station hardware with basic user interface (M20) M1.4: Working Central Station hardware with basic user interface (M20) M1.5: Intermediary report for D1.6: Scene description algorithms (M30) M1.6: Algorithms for automatic detection of abnormal behaviour based on audio, video and other signals (M35) M1.7: The methodology and model for data gathering (M36) M1.8: End-user Interface following the specification (M45) M1.9: Prototypes of Node Stations ready to be installed in selected agglomerations (M50) M1.10: Completed set of documentations and manuals, published scientific papers (M60)

43 GUT Task 1 suggestions We strongly encourage the usage of PLONE portal for work coordination:

44 GUT Task 1 suggestions Task 1. Framework of the System for secure data gathering and transmission: 1.1. Node Station (NS) – GUT (M5-M20) : Miniaturized weatherproof computers with cameras, microphones, other sensors connected (biometric sensors, cell phones identification, transmission scanners, monitoring devices, GPS, micro-transmitters, RFID tags) NS preparation NS construction Sensor data acquisition interfaces Installation of computers and cameras Integration of external devices (microphones, sensors, receivers, etc.) Data transmission to servers Mounting in waterproof enclosures NS maintenance (remote controlling, software updating)

45 GUT Task 1 suggestions 1.1. Node Station (NS) – GUT (M5-M20) : Processing of audio/video/other data Software framework for running various data processing and analysis algorithms as plug-ins Implementation of image analysis algorithms (object detection, object tracking, etc.) Data analysis from microphones, sensors, etc. Selection of important results of data analysis Encoding the data to a proper format Sending the data to the server

46 GUT Task 1 suggestions 1.1. Node Station (NS) – GUT (M5-M20) : Selection of the installation points Installation of NS in various points of city agglomerations and schools Testing (temperature, humidity, power loss, etc.) Calibration of the cameras for image analysis measurement of the video calibration points calculation of the image transformation parameters Algorithm for estimation of the physical object sizes from the calibrated camera images

47 GUT Task 1 suggestions 1.2. Central Station (CS) construction – GUT (M5-M20) : Main computer network build of: Administrator computer System management and maintenance Operators computers, providing: A map Audio and video live feeds Audio and video archive with searching A cluster of computers for analysis of data from multiple NSs

48 GUT Task 1 suggestions 1.2. Central Station (CS) construction – GUT (M5-M20) : Communicated with mobile terminals Multimedia/voice/data transmission from/to mobile terminals Sending event notifications to mobile terminals Receiving new events from mobile terminals Send alarms and other information to terminals Transmission protocols with data encryption Remote controlling of NSs from CS NS administration, diagnosis, configuration Turning on/off various plug-ins Controlling the cameras (field of view, image quality) Changing the mode of operation of NSs and the connected devices Remote software updating

49 GUT Task 1 suggestions 1.2. Central Station (CS) construction – GUT (M5-M20) : Interface to a database of audio-video recordings and detected events Searching events based on various criteria Viewing and exporting multimedia data associated with events User interface for: Query creation, Searching the database, Presentation of search results Database maintenance (archiving, cleaning)

50 GUT Task 1 suggestions 1.3. Methodology for scene description – PSI, GUT (M11-M30) : Integration of data analysis results from different NSs and multiple cameras Detecting large-area events engaging many NS (based on their geographical position)

51 GUT Task 1 suggestions 1.3. Methodology for scene description – PSI, GUT (M11-M30) : Integration of results of camera image analysis with audio analysis results and data from sensors, scanners, mobile terminals and other devices using scene description language Finding a relation between various data types Creation of descriptions containing data from multiple sources, related to the same events Development of an algorithm for automatic scene description based on combined data analysis results from multiple sources

52 GUT Task 1 suggestions 1.3. Methodology for scene description – PSI, GUT (M11-M30) : Development of the ‘language’ and tools for automatic description of the scene Description of objects and their relations with each other and with scene background

53 GUT Task 1 suggestions 1.3. Methodology for scene description – PSI, GUT (M11-M30) : Selection of the description format (XML) Creating of a ‘language’ for scene description (XML schema)

54 GUT Task 1 suggestions 1.3. Methodology for scene description – PSI, GUT (M11-M30) : Methods for analysis of the scene descriptions for automatic event detection Event definitions Event reporting

55 GUT Task 1 suggestions 1.4. Real-time secure data transmission to the CS and then to Police mobile terminals – Apertus, Moviquity, TUKE, GUT (M37-M50) Communication system architecture Devising architecture allowing for robust, reliable communication between system entities Transmission protocols Deciding upon choice of protocols which fulfill system requirements (security, real-time characteristics, etc.)

56 GUT Task 1 suggestions 1.4. Real-time secure data transmission to the CS and then to Police mobile terminals – Apertus, Moviquity, TUKE, GUT (M37-M50): Data security Emphasis on inclusion of proven security mechanisms to prevent unauthorized access, eavesdropping or system compromise System applications Deciding upon set of application, e.g: media streaming, offline file transfer, real time communication

57 GUT Task 1 suggestions 1.4. Real-time secure data transmission to the CS and then to Police mobile terminals – Apertus, Moviquity, TUKE, GUT (M37-M50): Arbitrary data transfer Support for transfer of arbitrary data throughout use of self- describing schemata (such as XML) Extensible, open framework Ability to introduce new entities (and new kinds of entities) within the communications system

58 GUT Task 2 suggestions Task 2. Analyzing, defining and integrating new and current technologies used for image, video and voice recognition and extraction, especially for: 2.1. Defining and recognizing particular audio signals (calling for help in European languages, shooting, etc.) – PSI, TUKE, GUT (M1-M25): Automatic analysis of audio stream directly on NS hardware Detection of potentially dangerous sound (e.g. braking glass, gunshots, screaming, calling for help in different languages) Alert generation in Central Station

59 GUT Task 2 suggestions 2.2. Creating algorithms for acquisition and pre- processing of audio and image signals – PSI, TUKE, INNOTEC, GUT (M1-M25): Video acquisition from multiple cameras (wide angle and pan-tilt-zoom cameras) Identification of region of interest (e.g. event detected in wide angle camera image) Controlling PTZ cameras to automatically view and track a region of interest or selected object

60 GUT Task 2 suggestions 2.2. Creating algorithms for acquisition and pre- processing of audio and image signals – PSI, TUKE, INNOTEC, GUT (M1-M25): Video pre-processing algorithms: Camera movement compensation Compensation of backlight changes (sunlight) Compensation of camera shake (wind, vibrations) Reduction of noise (especially at night – high color noise) Other preprocessing algorithms Running the low-level analysis of pre-processed images (object detection and tracking) Selection of data for further processing Sending the selected data to high-level processing modules (event detection and interpretation)

61 GUT Task 2 suggestions 2.2. Creating algorithms for acquisition and pre- processing of audio and image signals – PSI, TUKE, INNOTEC, GUT (M1-M25): Classification of important events in video and audio stream for archiving and processing Analysis of detected events Event filtering – discarding unimportant events Sending important events to modules for event analysis and interpretation Sending the results to be archived in the database

62 GUT Task 2 suggestions 2.2. Creating algorithms for acquisition and pre- processing of audio and image signals – PSI, TUKE, INNOTEC, GUT (M1-M25): Determining sound DOA (direction of arrival) with microphone matrix Allows moving PTZ camera to the point where sound event came from

63 GUT Task 2 suggestions 2.3. Implementing methods for extracting human biometric features from images - GUT, PUT (M1-M25): Parameterization (analysis and description) of human posture and action for detection of a threat Algorithms for face detection in the video image

64 GUT Task 2 suggestions 2.3. Implementing methods for extracting human biometric features from images - GUT, PUT (M1-M25): Specialized human detection algorithms in video images Individual people detection and counting in crowded scenes Analysis of behavior of detected persons Extraction of biometric features describing the detected persons Selection of the important biometric features Processing of the selected parameters

65 GUT Task 2 suggestions 2.4. Implementing image analysis, motion tracking and object detection – FHTW, GUT (M1-M25): Tracking of moving objects Continuous unambiguous tracking of every object present in a camera field of view Recognition of the same objects in images from different cameras (with overlapping or non-overlapping fields of view) Background separation – detection of moving objects Removing unimportant parts (shadows, etc.) Tracking the movement of the detected objects Processing the results of object tracking Tracking objects in multiple camera images

66 GUT Task 2 suggestions 2.4. Implementing image analysis, motion tracking and object detection – FHTW, GUT (M1-M25): Classification of moving objects Selection of object classes Extraction of parameters relevant to classification Creating rules for dividing the objects into classes Labeling of the objects Dividing detected objects into a few main categories (humans, animals, vehicles, non-moving objects Determining vehicle type (e.g. truck, car, single-track vehicle)

67 GUT Task 2 suggestions 2.4. Implementing image analysis, motion tracking and object detection – FHTW, GUT (M1-M25): Discarding unimportant objects from further analysis Determining objects (false detections, animals etc.) which are not important from the surveillance point of view Description of the relevant objects (e.g. only humans) Analysis of the tracked objects Detection of basic events in the camera images (objects’ behavior) Implementation of object detection, tracking and classification Detection of basic events (object appeared/disappeared, object stopped/moved, change in direction of the movement, objects combined/separated, etc.)

68 Navigate back to other Partners

69 Report from WP1 End-users requirements! – parallel with WP7 FHTW – 2.4 task discussed and approved PUT – human face recognition AGH – Piotr Romaniak – video quality of experience assessment and optimization - New subtask Audio quality – New subtask NS installation abroad WP1 (WP7, WP8 also) work meeting in Spring in Gdansk Some mistakes in DoW detected (PSI roles, PSNI)


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