Just In
- 19 min ago Gigabyte Unveils AORUS CO49DQ: A Curved QD-OLED Gaming Monitor for Immersive Entertainment
- 20 min ago Oppo K12 Launched with Snapdragon 7 Gen 3 SoC, 120Hz AMOLED Display, 100W Charging
- 42 min ago Meta Ray-Ban Smart Glass Users Can Now Make Video Calls on WhatsApp
- 2 hrs ago Realme Narzo 70 5G, Narzo 70x 5G Launched in India: Check Price, Specs, Availability
Don't Miss
- Automobiles Ultraviolette F77 Mach 2 Launched At Rs 2.99 Lakh - 323km Range, More Power & Tech
- Education Maharashtra Class 10th Result 2024 to be Released Soon; Check Minimum Marks Required to Qualify Maharashtra SS
- Finance 1:10 Split, 5 Bonus, 70% Dividend: Crorepati Defene PSU Hits New High, 108605% Returns; BUY For Long Term
- Movies Deadpool & Wolverine Cast Fees: Ryan Reynolds' Salary 150% HIGHER Than Hugh Jackman; Guess MULTI-CRORE Fees
- Sports DC vs GT My11Circle Prediction IPL 2024 Match 40: DEL vs GUJ Fantasy Tips & Expert Picks
- News Tamil Nadu Weather Update: 9 Districts Over 40°C, Salem Boils At 42.3°C; Heatwave Warning Issued
- Travel Mumbai Opens BMC Headquarters For Exclusive Heritage Tour
- Lifestyle Summer Style: 6 Must-Try Colors To Stay Fashionably Cool Like B-Town Divas!
Robotic Camera Mimics Humans to Track Basketball Action
New York, Jan 8 (IANS) Scientists at Disney Research Lab, Pittsburgh, have developed robotic cameras that mimic human operators to anticipate basketball game action and learn how to better frame shots of a game.
Peter Carr, a Disney Research engineer, and Jianhui Chen, Ph.D. student in computer science at the University of British Columbia, devised a data-driven approach that allows a camera system to monitor an expert camera operator during a basketball game.
The automated system uses machine learning algorithms to recognise the relationship between player locations and corresponding camera configurations.
"We do not use any direct information about the ball's location because tracking the ball with a single camera is difficult," Carr said.
"But players are coached to be in the right place at the right time, so their formations usually give strong clues about the ball's location," he added.
Recommended: Top 10 Upcoming Rumored Smartphones Expected To Launch in 2015
Carr and Chen demonstrated their system on a high school basketball game.
They used two cameras - a broadcast camera that was operated by a human expert and another that was a stationary camera that the computer used to detect and track the players automatically.
Following supervised learning based on the operator's actions, the system was able to predict how to pan the camera in a way that was superior to the best previous algorithm and that did indeed mimic a human operator.
"The method can be adapted to other sports possibly with additional features," Carr noted.
Future work will also include mimicking the auxiliary cameras used for cutaway shots in multi-camera productions.
The team was scheduled to report their findings at "WACV 2015", the IEEE Winter Conference on Applications of Computer Vision at Waikoloa Beach, Hawaii this week.
Source: IANS
-
99,999
-
1,29,999
-
69,999
-
41,999
-
64,999
-
99,999
-
29,999
-
63,999
-
39,999
-
1,56,900
-
79,900
-
1,39,900
-
1,29,900
-
65,900
-
1,56,900
-
1,30,990
-
76,990
-
16,499
-
30,700
-
12,999
-
26,634
-
18,800
-
62,425
-
1,15,909
-
93,635
-
75,804
-
9,999
-
3,999
-
2,500
-
3,599