원본/출처 : http://www.mckinsey.com/industries/high-tech/our-insights/video-meets-the-internet-of-things?cid=eml-web
출처 : http://m.inews24.com/view.php?g_serial=995673&g_menu=020100&rrf=nv
언제 부터 인지 강제(!) 광고 듣기가 많아지기 전까지는 최고의 무료 음원 서비스 중 하나였는데 결국 사업성과 투자 확보에 실패해서 서비스가
3년 만에 중단되었다고 합니다. STRTUP 생성-> 실패 -> 성공이 자연스러운 생태계 발전의 모습이지만 최근에 계속 나오는
STARTUP 실패 이야기는 우울하기만 합니다.
A common misunderstanding in today’s security world is that video analytics is restricted to fixed cameras, when in fact; the ability to utilize video analytics on in-motion pan-tilt-zoom (PTZ) cameras has been available for many years. It is not until recently, however, that the capability to perform video detection while a PTZ camera is in full motion has become more readily available to security integrators and dealers. This capability, also referred to as motion detection while scanning, has been slow to commercialization partly due to the complexity of the solution, and the limited number of manufacturers that have addressed the technical hurdles. Today, there are several commercially viable solutions on the market, opening a new era of automated video surveillance and detection.
Video Analytics is the ability to analyze a live or recorded video feed and intelligently extract useful data concerning what is happening in the scene. This is a widely used capability for the protection of critical facilities and assets. Types of video analytics vary greatly, from simple detection, object classification, counting, monitoring for removed objects to loitering detection. The ability to utilize these algorithms to automatically provide insight to security personnel has proven to be a valuable tool. Although there are many types of video analytics available, most algorithms used in today’s security environment have been limited to fixed cameras and fixed scenes. This is unfortunate for security personnel as the PTZ camera continues to remain one of the most powerful tools in the security arsenal. This is partly due to the camera’s ability to point in any direction and at many zoom levels, allowing the security person to cover a large area without the need for many additional fixed sensors. This is an important capability, as a vast amount of any facility is typically not covered with full time video surveillance. This continued reliance on the PTZ camera has driven an increased demand to utilize video analytics on in-motion PTZ cameras. Although many different solutions are available, in-motion video analytics remain a complex task with several technical hurdles.
Understanding Frame of Reference: At its most basic premise, detection using video analytics is about understanding changes in pixels. However, to avoid alarming on pixel changes due to lighting, shadows or falling leaves, video analytic algorithms need to understand some details of the scene. Understanding that a pixel, or several pixels, represents a very small object (a leaf) or a large object (a vehicle), is critical to understanding what is a real item of interest, versus nuisance motion. Knowledge of the horizon, or geospatial data, is also extremely useful. The amount of scene information required varies greatly over the spectrum of video analytic solutions, but in all cases, some details of the scene must be communicated to the algorithm during setup.
원본링크 : http://www.puretechsystems.com/blog/using-video-analytics-with-pan-tilt-zoom-cameras/
M&A통해 SECURITY 사업분야 확대를 하고 있는 미국 FLIR 회사의 최근 M&A 소식이 놀랍습니다. DRONE업체 PROXY DYNAMIC사를 인수했다는 소식이 그 전의 어떠한 인수 합병 (DVTEL, POINTGRAY, ISD) 소식 보다 기대가 됩니다.
아직 미국보다 활용과 적용의 속도와 중국보다 느린 DRONE 기술 개발의 속도가 느린 한국제품의 분발이 필요한것
같습니다. ISC WEST 2017 전시회에는 별도 DRONE 전시 코너도 생긴다고 합니다.
NEWS LETTER로 받아보는 IPVM뉴스에서는 중국제조 카메라들의 보안문제 관련 글들이 계속되고 있었습니다.
제조 국가가? 제조사가 어디인가를 떠나서 PUBLIC망에서 영상 자체의 보안 수단이 없는 공통된 상황에서 카메라 자체의 보안 이슈만 제기하는
것이 무슨 소용이 있나 생각을 하게 됩니다. 물론 IPVM에서 제기된 문제는 카메라 내부에 있는
공격 성 sw의 문제제기라서,, 관점이 다르긴 합니다. 그 논란의 결과인지 몰라도 아래 뉴스들이 최근에 연이어 알려지고 있습니다.
출저 : IPVM (https://ipvm.com/)
출처 : https://www.linkedin.com/pulse/trigs-xload-sensor-wins-astech-award-peter-stunden?trk=prof-post
TRIG's XLOAD Sensor Wins ASTech Award 2016