… The future-of-the-sport stuff will likely stick for a while, and it’s not just because Pugh was called up to the U20 national team at the age of 16 and went on to become the youngest player for the USWNT to score an Olympic goal, or because she scored 15 of them by the time she was old enough to drink. Rather, it’s because amid all of that, she blazed her own path. After briefly enrolling at UCLA, Pugh decided to forgo NCAA soccer and enter the National Women’s Soccer League, and she was later drafted by the Spirit. Going pro early is the norm for American men; not long ago, Pennsylvania whiz kid Christian Pulisic decamped for Germany’s Borussia Dortmund at the age of 16. But women in the U.S. rarely make the leap.
“I think it’s fantastic,” USWNT head coach Jill Ellis says. “We have to get to a point in this country where our top players are seeking out the most challenging environments.”
Ellis watched Pugh for the first time at a U14 national camp and was immediately taken by the young player, a fearless attacker who wove through packs of older girls like she was riding a scooter in traffic. Since then, Ellis says Pugh has improved both her technique and her tactical ability. In the World Cup, she will likely come off the bench — the team is stacked up front, with Megan Rapinoe, Alex Morgan and Tobin Heath on the roster — but Ellis sees the team’s youngest attacker as a potent weapon. When I ask her what role Pugh might play in France, she paints a picture. “You’re in the 70th minute and you’re exhausted and suddenly Mal Pugh is running at you,” she says, adding, “She doesn’t have to take the weight of the world on her shoulders right now.”
… if there’s anything the 23-year-old reliever has learned through the three torn ACLs in three years, the three elbow surgeries, the junior college years and the months he needed assistance going to the bathroom, it’s that his career is always one pitch away from being finished.
Every time Moffitt walks into Alex Box Stadium, every time he’s screaming absurdities in the huddle, every time he throws a pitch, he operates under the assumption he could suffer that final injury to end his career at any moment.
So now, as the end point in Moffitt’s career becomes real with Senior Day on Saturday (May 18), one can’t help but look back at Moffitt’s nonsensical seven-year journey to this point and wonder:
Last week, the Mountain West hosted a first-ever meeting of its kind nationally, the 2019 MW Head Football Coaches and Referee Officiating Summit in Colorado Springs, Colorado. This two-day meeting, which was attended by MW head coaches, seven referees, Greg Burks (MW Coordinator of Football Officials), Rogers Redding (NCAA’s National Coordinator of Football Officials) and Conference staff, was intended to develop a better understanding and have dialogue regarding rules, philosophies and officiating mechanics between the two groups.
“I think we are doing something that is really unique,” said Wyoming head coach Craig Bohl. “There is no doubt in my mind, a lot of my colleagues around the country when they hear this, they’re going to say ‘that’s a heck of an idea.’”
ChyronHego today introduced TRACAB Gen5, the newest generation of the company’s Emmy® Award-winning TRACAB optical sports tracking system. TRACAB Gen5 features significant improvements in tracking data quality and accuracy, driven by completely redesigned tracking algorithms, a richer array of camera angles, and powerful new AI features for player, number, and colour recognition.
TRACAB Gen5 uses a distributed system of cameras installed around the field of play and advanced image processing technology to capture and deliver real-time tracking data on the movements of each player, referees, and the ball. As the world’s most widely deployed optical sports tracking system, TRACAB has been installed in over 300 stadia and is currently used to capture live tracking data for more than 4,500 football/soccer and baseball games each year.
This past September, Jenny Simpson headed out in the rain to the start of the 5th Avenue Mile road race with two pairs of running shoes in her bag. One was trusted and familiar: a pair of New Balance Hanzo S’s that she’d worn while winning on this course before. They fit her; they worked. The race is one of the most prestigious in the country, and she’d triumphed in it an astonishing five times in a row. In elite racing—as in much else in life—the gear on your feet always matters less than the buzzards in your mind. Why wear something new that might create stress?
Her sponsors at New Balance, though, were rooting for a different choice. They wanted her to go with Rick and abandon Victor Laszlo. Because the second pair in her bag was a strange test shoe. It weighed just five ounces, which is 20 percent lighter than the Hanzo S, and included a new special kind of responsive foam stretching from heel to forefoot. It also had a small carbon-fiber plate running from the front of the heel to the big toe. When Simpson had first put them on, she’d felt wobbly and bizarre, like the middle of her heels weren’t touching the ground. She remembers thinking, when she tried it, that she’d end up fighting the designers. “They are going to engineer this to the moon, and it’s going to not be something I’m comfortable with.”
arXiv, Computer Science > Robotics; Andrey Rudenko, Luigi Palmieri, Michael Herman, Kris M. Kitani, Dariu M. Gavrila, Kai O. Arras from
With growing numbers of intelligent systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing approaches based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.
Sensors in pucks, sticks, uniforms will transform coaching and viewing with real-time analytics.
It’s hard to imagine a faster-paced sport than hockey. Other than penalty calls and faceoffs, hockey is pretty much non-stop action for a full hour broken into three 20-minute periods. By comparison, a professional football game may last three to four hours, but the amount of time when there’s actual action occurring on the field pales in comparison to a hockey game.
Now the National Hockey League (NHL) is moving toward taking analytics that can be gathered in real time during a game to a whole new level.
Comcast is working on an in-home device to monitor people’s health, and aims to begin pilot-testing it later this year.
A team under Sumit Nagpal, a senior vice president and general manager of health innovation at Comcast who previously worked at the consulting firm Accenture, has been working on the device for more than a year, according to two people with direct knowledge. Nagpal joined Comcast in February of this year, according to LinkedIn, to build a strategy and a team for bringing the new health hardware to market.
KINEXON and RSPCT have announced a seamless product integration between their innovative technologies. The integrated solution combines player’s performance analytics & positioning from KINEXON with precise shot tracking from RSPCT, all in real-time. All RSPCT data is automatically synchronized and visualized in the KINEXON App and can be fully analysed live and after each training and game, while all of RSPCT’s shots are automatically assigned to the players.
University of California, Berkeley ; Angjoo Kanazawa, Jason Y. Zhang, Panna Felsen, Jitendra Malik from
From an image of a person in action, we can easily guess the 3D motion of the person in the immediate past and future. This is because we have a mental model of 3D human dynamics that we have acquired from observing visual sequences of humans in motion. We present a framework that can similarly learn a representation of 3D dynamics of humans from video via a simple but effective temporal encoding of image features. At test time, from video, the learned temporal representation can recover smooth 3D mesh predictions. From a single image, our model can recover the current 3D mesh as well as its 3D past and future motion. Our approach is designed so it can learn from videos with 2D pose annotations in a semi-supervised manner. However, annotated data is always limited. On the other hand, there are millions of videos uploaded daily on the Internet. In this work, we harvest this Internet-scale source of unlabeled data by training our model on them with pseudo-ground truth 2D pose obtained from an off-the-shelf 2D pose detector. Our experiments show that adding more videos with pseudo-ground truth 2D pose monotonically improves 3D prediction performance. We evaluate our model on the recent challenging dataset of 3D Poses in the Wild and obtain state-of-the-art performance on the 3D prediction task without any fine-tuning.
Thermoregulation has substantial implications for energy consumption and human comfort and health. However, cooling technology has remained largely unchanged for more than a century and still relies on cooling the entire space regardless of the number of occupants. Personalized thermoregulation by thermoelectric devices (TEDs) can markedly reduce the cooling volume and meet individual cooling needs but has yet to be realized because of the lack of flexible TEDs with sustainable high cooling performance. Here, we demonstrate a wearable TED that can deliver more than 10°C cooling effect with a high coefficient of performance (COP > 1.5). Our TED is the first to achieve long-term active cooling with high flexibility, due to a novel design of double elastomer layers and high-ZT rigid TE pillars. Thermoregulation based on these devices may enable a shift from centralized cooling toward personalized cooling with the benefits of substantially lower energy consumption and improved human comfort.
The NFL and the NFLPA announced the formation of two committees targeting player pain management, mental health and wellness—which will study the use of marijuana for pain. But don’t expect change to be swift.
Around these parts I’m known as a bit of a vitamin junkie. While I’m not choking down a dozen vitamins a day like you get in those gas station packets, I do use myself as a bit of a wide-eyed guinea pig to see if supplements can improve my life. Over the years I’ve taken vitamin B (said to be great for energy and brain function), vitamin D (good for bone health; a deficiency is common), vitamin C (the miracle vitamin), milk thistle (said to improve liver function), and any number of additional supplements that have come in and out of my life. On one occasion many years ago I bought piracetam at a farmacia in Mexico because I read it would make you smarter. The jury remains out on that.
And so, when a new company called Baze pitched me that it was offering a bespoke vitamin service based on an at-home blood test, I was immediately onboard. All the vitamins and supplements I’ve taken to date were driven by hunches, hearsay, and breathless headlines from Parade magazine. Now someone was going to actually bring medical science into the mix. Sign me up.
I often get asked, “How do people come up with research ideas?” Everyone has their own techniques, but I’ve noticed some common patterns throughout the years. In the spirit of software design patterns, here are some design patterns for academic research that I’ve seen in fields near mine. Although there are many great examples from others, I’ll use some of my own papers as examples here because I don’t want to speculate about how others came up with their ideas; all I know is how I’ve come up with mine!
Lots of research advice basically boils down to “come up with something new that nobody else has thought of yet.” This kind of advice is way too vague, so I’m trying to make it more concrete by listing a set of design patterns. Note that these patterns don’t dictate a specific type of research contribution (e.g., an algorithm, toolkit, programming language, system, empirical study, data analysis, or theoretical analysis), although they were developed with engineering and technology research in mind.