SPECIAL NOTICE
A -- Video Management, Editing, and Analysis Tools
- Notice Date
- 2/12/2009
- Notice Type
- Special Notice
- NAICS
- 541690
— Other Scientific and Technical Consulting Services
- Contracting Office
- Office of the Chief Procurement Officer, Washington, District of Columbia, 20528, United States
- ZIP Code
- 20528
- Solicitation Number
- RFI-09-10--STIDP-VideoMgmt
- Response Due
- 3/13/2009
- Archive Date
- 3/28/2009
- Point of Contact
- Albert J Dainton,, Phone: 202-254-6371
- E-Mail Address
-
albert.dainton@dhs.gov
- Small Business Set-Aside
- N/A
- Description
- Request for Information: Video Management, Editing, and Analysis Tools PROGRAM DESCRIPTION The Department of Homeland Security, Science and Technology Directorate (DHS-S&T), Explosives Division, has been tasked to conduct operational field demonstrations of remotely operated and standoff explosives countermeasure technologies to address the threat from suicide bomber, leave-behind, and vehicle-borne improvised explosive devices. DHS-S&T’s Standoff Technology Integration and Demonstration Program (STIDP) is designed to accelerate the development of standoff explosives detection technologies, related technologies, concept of operations, and training. The ultimate goal of the program is to prevent explosives attacks at large public events via a spiral development approach to technology and systems development. The STIDP is planning to conduct multiple field tests, with the earliest possible time being summer/fall, 2009. The intent of the field test is to evaluate an integrated people-tracking system/concealed object detection system as part of an overall countermeasure architecture to determine system and individual sensor technical performance, integration approaches, and concept of operations effectiveness in a live, operational environment. PROBLEM STATEMENT The program requires that sensor and surveillance camera video be generated, displayed, recorded, archived, and mined over a network for key test parameters. During live operations, video data generated will be displayed and recorded over a network in real time. Archiving and mining of the data will take place after live operations have been terminated and may be performed from multiple workstations. The program is interested in using a system for the flexible and cost-effective management, editing, and analysis of the video data. Management of the video data will include the automatic recording and storage of the video as well as providing the ability to view playbacks of the video data on networked workstations based upon user-defined date and time criteria. The video storage portion of the system will be required to automatically manage video datasets based upon date and time criteria as well as the source of the recordings. Sources supplying video feeds to the system will include various camera types (e.g. surveillance and infrared) as well as other sources such as software interface image captures, and sensors. The storage of data must be non-proprietary in format, allowing the data to be accessed and viewed by third-party software applications. The storage of data also needs to be machine-independent. Data archives managed by the system should allow for the movement of the datasets to various machines or networks without the need to create exported subsets of the data. Desired editing functionality includes the ability to create high-quality, high-resolution video clips from the video dataset based upon user-defined data and time criteria. The system should allow for the exportation of video clips in various formats such as.avi and.mpg files and enable an analyst to add notations or markings to the video image. The system should allow for clipping of a section from a single video frame. Desired analysis capabilities include the ability to search for and play back video from one or more video sources during an active recording session as well as providing an automated manner in which to create statistics from the recorded video. These statistics may include time periods in which there is no movement present in the video as well as time periods of heavy movement. The desired analysis tools would also provide a means to perform pattern matching which would allow for the flagging of time periods in which large groupings of people are present in the field of view as well as periods in which pedestrians or objects are moving counter to the traffic flow. The tools should also provide a means to tie textual information to the individual video datasets. This textual information may include notations from analysts as well as alert descriptions and definitions generated by third-party sensors or software. Some of the key challenges for video data management include: 1)Processing, storage, and transferring large video datasets 2)Accepting input from a dynamic number of sources as well as source types (cameras, s-video) 3)Providing the ability to play back video during the testing process while continuing to record and process incoming datasets Ultimately, implementation of a video management, editing, and analysis system (which may include more than one technology) should address these features: 1)Easily scalable to any number of input sources 2)Provides high-resolution, high-quality video exports in multiple formats (e.g..avi,.mpeg,.mov) Provides portable datasets that can be viewed on multiple computers simultaneously 3)Provides non-proprietary datasets that can be accessed or viewed by third-party software applications 4)Integrates non-video meta-data with video data through the use of date and time stamps 5)Provides editing and analysis functionality of video datasets 6)Provides the ability to generate statistics based upon patterns found in the video data. REQUIREMENTS Operating Environment oProvide simultaneous access to multiple computers on a network without significantly degrading other network traffic oAllow viewing of recorded data while real-time video is being recorded oAllow random-access searching and viewing based upon date and time criteria oProvide documented, easy-to-learn-and-use graphical user interface oOperate in a Windows-based operating system Tracking Requirements oProvide the ability to easily and dynamically add and remove video sources with minimal changes to the system’s configuration oProvide a means to archive or back up the video data over a network oProvide the ability to set custom archiving and processing schedules oAllow the movement of archived data from one location to another without losing the ability to access and process the data oProvide the means to search the data sets based upon time or alert indices oProvide the ability to easily create high-quality exports of video segments in multiple video file formats oProvide the means to analyze and mine video data oProvide the means to perform self diagnostics oAllow for real-time playback oProvide the ability to create custom views of the data oProvide multi-sensor and camera views during real-time events and post events INTERESTED PARTIES Parties with people-tracking systems that can address the problems and requirements above are encouraged to respond with a white paper. Please limit submission to a maximum of 5 pages in length (including a cover sheet) and provide the following information: Cover Page (Page 1) •Contact and Company Information oName oTitle oCompany name oDate of incorporation oFY08 sales oNumber of employees oLocation oMailing address oPhone number oWeb page address oEmail address •Name/type of technology •Technology readiness level of the existing technology or technology concept •Technology summary covering technical approach, operating principles, testing conducted to date, and commercial sales, if any Page 2-5 •Technical background on how the technology works, and number and type of components •Whether or not the technology is suitable for use outdoors with large crowds •Overview of how the technology would be deployed in an operational setting, including hardware, software and manpower requirements •Overview of the test and evaluation activities conducted to date and how this data supports performance claims •Current ongoing R&D and sources of funding (including amounts) •Schedule for anticipated technology upgrades and associated testing •How the technology is or has been or can be integrated with other sensor technologies to improve the overall countermeasure performance •Government/academia/industrial partners or potential partners •Previous work performed in the subject area being proposed, including but not limited to work performed for the U.S. government or other federal agencies (including international) • How your technology would need to be adapted or integrated with other concealed object detection technologies to provide a viable solution •Description of the concealed object detection technologies that could be integrated with your technology to provide a viable solution Marketing brochures, fliers, published presentations or papers, etc. that summarizes the technology and more about your company are encouraged in addition to the white paper, but should not be substituted as a replacement for the white paper. Responses to this request for information are to be submitted electronically to Pacific Northwest National Laboratory at stidp-rfi@pnl.gov. Please include in the subject line the number of the RFI you are responding to.
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