Chandrashekhar N. Padole

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Among the available biometric traits such as face, iris and fingerprint, there is an active research being carried out in the direction of unconstrained biometrics. Periocular recognition has proved its effectiveness and is regarded as complementary to iris recognition. The main objectives of this paper are threefold: 1) to announce the availability of(More)
—Motion Tracking has been applied in many recent applications like surveillance, advance driver assistance system (ADAS), non-cooperative biometrics, virtual reality, etc. Current research in this field includes making tracking system more robust and reliable. Imaging modality to be used in motion tracking also includes thermal imaging (FIR) in addition to(More)
Using information near the human eye to perform biometric recognition has been gaining popularity. Previous works in this area, designated periocular recognition, show remarkably low error rates and particularly high robustness when data are acquired under less controlled conditions. In this field, one factor that remains to be studied is the effect of(More)
The state-of-the-art gait recognition algorithms require a gait cycle estimation before the feature extraction and are classified as periodic algorithms. Their effectiveness substantially decreases due to errors in detecting gait cycles, which are likely to occur in data acquired in non-controlled conditions. Hence, the main contributions of this paper are:(More)
In the context of less constrained biometrics recognition, the use of information from the vicinity of the eyes (periocular) is considered with high potential and motivated several recent proposals. In this paper, we focus on two factors that are known to degrade the performance of periocular recognition: varying illumination conditions and subjects pose.(More)
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