Image Recognition  

With the new release of a cloud-based image recognition system API from Google, developers will be empowered to build new applications that can see, and more importantly understand, the content of images. The company showed off the software with a simple robot that can recognize objects like a banana, and a user's smiling face.

Google recently announced the launch of Cloud Vision, one of the company’s image recognition technologies. They have made it available to developer as an API with a limited preview available using the Google Cloud Platform.

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"The uses of Cloud Vision API are game changing to developers of all types of applications and we are very excited to see what happens next," writes Ram Ramanathan, Product Manager for the Google Cloud Platform.

Google’s image recognition technology is one of the strongest around, applicable to many domains that include optical character recognition (OCR), face detection, and object recognition.

The Cloud Vision API quickly classifies images into thousands of categories, detects faces with associated emotions, and recognizes printed words in many languages. Developers using the Cloud Vision API, will be able to build metadata into an image catalog, to moderate offensive content, or enable new marketing scenarios through image sentiment analysis.

The following set of Google Cloud Vision API features can be applied in any combination on an image:

• Label/Entity Detection picks out the dominant entity (e.g., a car, a cat) within an image, from a broad set of object categories. You can use the API to easily build metadata on your image catalog, enabling new scenarios like image based searches or recommendations.

• Optical Character Recognition to retrieve text from an image. Cloud Vision API provides automatic language identification, and supports a wide variety of languages.

• Safe Search Detection to detect inappropriate content within your image. Powered by Google SafeSearch, the feature enables you to easily moderate crowd-sourced content.

• Facial Detection can detect when a face appears in photos, along with associated facial features such as eye, nose and mouth placement, and likelihood of over 8 attributes like joy and sorrow. We don't support facial recognition and we don’t store facial detection information on any Google server.

• Landmark Detection to identify popular natural and manmade structures, along with the associated latitude and longitude of the landmark.

• Logo Detection to identify product logos within an image. Cloud Vision API returns the identified product brand logo, with the associated bounding polybox.

To demonstrate a simple example of the Vision API, Google developers have built a working Raspberry Pi based platform with just a few hundreds of lines of Python code, calling the Vision API. 

As the video below shows, the demo robot can roam and identify objects, including smiling faces.

Cloud Vision is partially powered by Google's TensorFlow machine learning platform that was recently open-sourced.

SOURCE  Google

By 33rd Square

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 Human-Computer Interation  

Human emotion can be transferred by technology that stimulates different parts of the hand without making physical contact with your body, according to a new study.

Human emotion can be transferred by technology that stimulates different parts of the hand without making physical contact with your body, a University of Sussex-led study has shown.

Sussex scientist Dr. Marianna Obrist, Lecturer at the Department of Informatics, has pinpointed how next-generation technologies can stimulate different areas of the hand to convey feelings of, for example, happiness, sadness, excitement or fear.

For example, short, sharp bursts of air to the area around the thumb, index finger and middle part of the palm generate excitement, whereas sad feelings are created by slow and moderate stimulation of the outer palm and the area around the ‘pinky’ finger.

The findings, which will be presented at the CHI 2015 conference in South Korea, provide “huge potential” for new innovations in human communication, according to Dr Obrist.

According to Obrist, "Imagine a couple that has just had a fight before going to work. While she is in a meeting she receives a gentle sensation transmitted through her bracelet on the right part of her hand moving into the middle of the palm. That sensation comforts her and indicates that her partner is not angry anymore.

“These sensations were generated in our experiment using the Ultrahaptics system.

“A similar technology could be used between parent and baby, or to enrich audio-visual communication in long-distance relationships.

“It also has huge potential for ‘one-to-many’ communication – for example, dancers at a club could raise their hands to receive haptic stimulation that enhances feelings of excitement and stability.”

Using the Ultrahaptics system – which enables creating sensations of touch through air to stimulate different parts of the hand – one group of participants in the study was asked to create patterns to describe the emotions evoked by five separate images: calm scenery with trees, white-water rafting, a graveyard, a car on fire, and a wall clock. The participants were able to manipulate the position, direction, frequency, intensity and duration of the stimulations.

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A second group then selected the stimulations created by the first group that they felt best described the emotions evoked by the images. They chose the best two for each image, making a total of 10.

Finally, a third group experienced all 10 selected stimulations while viewing each image in turn and rated how well each stimulation described the emotion evoked by each image.

The third group gave significantly higher ratings to stimulations when they were presented together with the image they were intended for, proving that the emotional meaning had been successfully communicated between the first and third groups.

Now Obrist has been awarded £1 million by the European Research Council for a five-year project to expand the research into taste and smell, as well as touch.

The SenseX project will aim to provide a multisensory framework for inventors and innovators to design richer technological experiences.

Obrist said, “Relatively soon, we may be able to realise truly compelling and multi-faceted media experiences, such as 9-dimensional TV, or computer games that evoke emotions through taste.

“Longer term, we will be exploring how multi-sensory experiences can benefit people with sensory impairments, including those that are widely neglected in Human-Computer Interaction research, such as a taste disorder.”



SOURCE  University of Sussex

By 33rd Square

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In the video below a demonstration of NAO movement by using Kinect by NAO Developer Zecloud and Taylor Veltrop from Aldebaran Robotics at the Microsoft Tech Days, Paris on 7th February 2012.  Not quite as impressive as the cat grooming demo, but impressive nevertheless.