Sentence examples for facial datasets from inspiring English sources

Experiments were carried out as follows: the facial datasets built in the experimental phase 1 was used to set the projection (through LDA), classification/regression (through SVM), and scaling models.

He describes it as a "simple script to scrape Tinder profile photos for the purpose of creating a facial dataset," saying his inspiration for creating the scraper was disappointment working with other facial data sets.

Why not leverage Tinder to build a better, larger facial dataset?" Why not — except, perhaps, the privacy of thousands of individuals whose facial biometrics you're dumping online in a mass repository for public repurposing, entirely without their say-so.

"Why not leverage Tinder to build a better, larger facial dataset?" he asked.

He touts it as a "simple script that exploits the Tinder API [app programming interface] to allow a person to build a facial dataset".

Two of the most commonly used facial expression datasets in current literature were selected for testing.

Many large facial image datasets have been developed, but most are targeted at facial recognition and have size on the order of several thousands [26 28].

Many of the existing facial expression datasets are composed of a set of posed face images not captured in a realistic affective-interaction setting.

The "pictures of facial affect" dataset is one of the most intensively studied facial expression datasets of all times (e.g. Adolphs, 2002; Seitz et al., 2008).

Consequently, our facial color dataset is built up with a total of 122 cases, containing 24 normal color images, 15 for bluish, 18 for reddened, 24 for yellow, 21 for pale, and 20 for darkish color images.

The Japanese Female Facial Expression (JAFFE) dataset [47] contains 213 images of 10 female Japanese subjects.