%0 Journal Article %1 noauthororeditor %A K.Sunilkumar, %A T.KishoreKumar, %D 2013 %J International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI) %K LAB MAT SSP behavioral cluttered cues images intelligence interactions social %N 1 %P 10 %R 10.5121/ijscai.2013.2103 %T Advanced Human Behavioral Cues Detection: A Method in Social Signal Processing %U http://airccse.org/journal/ijscai/papers/0213scai03.pdf %V 2 %X Social Signal Processing (SSP) is the new research domain that aims at understanding social interactions and social intelligence. The essence of social intelligence is the ability to recognize human social signals and behaviors cues (verbal and non-verbal). We present a unified model for non-verbal behavioral cues SSP under the categories of face detection like eyes-mouth-lips-ears-nose, emotional assessments like anger-happy-sadness-neutral and physical appearance like height (short-average-tall), attractiveness (smartness) and body shape(slim-normal-flat) in real-world cluttered images which is one of the method in social signal processing. It is rather difficult task to detect and interpret temporal patterns of nonverbal behavioral cues in a given context. Our main objective is to detect non-verbal behavioral cues by introducing advanced human behavioral cues detection method. Our proposed method shown a better results and practically applicable in the real world environment. We implemented our proposed method in MATLAB R2007b simulator and designed a GUI for our proposed method.

@article{noauthororeditor, abstract = {Social Signal Processing (SSP) is the new research domain that aims at understanding social interactions and social intelligence. The essence of social intelligence is the ability to recognize human social signals and behaviors cues (verbal and non-verbal). We present a unified model for non-verbal behavioral cues SSP under the categories of face detection like eyes-mouth-lips-ears-nose, emotional assessments like anger-happy-sadness-neutral and physical appearance like height (short-average-tall), attractiveness (smartness) and body shape(slim-normal-flat) in real-world cluttered images which is one of the method in social signal processing. It is rather difficult task to detect and interpret temporal patterns of nonverbal behavioral cues in a given context. Our main objective is to detect non-verbal behavioral cues by introducing advanced human behavioral cues detection method. Our proposed method shown a better results and practically applicable in the real world environment. We implemented our proposed method in MATLAB R2007b simulator and designed a GUI for our proposed method.}, added-at = {2020-02-28T10:28:03.000+0100}, author = {K.Sunilkumar and T.KishoreKumar}, biburl = {https://www.bibsonomy.org/bibtex/2abb4968abf622566cc94e05562b44d6b/leninsha}, doi = {10.5121/ijscai.2013.2103}, interhash = {ed2d4c3e12545df6554a15e50ad87a7e}, intrahash = {abb4968abf622566cc94e05562b44d6b}, issn = {2319 - 1015}, journal = {International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI)}, keywords = {LAB MAT SSP behavioral cluttered cues images intelligence interactions social}, language = {English}, month = {February}, number = 1, pages = 10, timestamp = {2020-02-28T10:28:03.000+0100}, title = {Advanced Human Behavioral Cues Detection: A Method in Social Signal Processing}, url = {http://airccse.org/journal/ijscai/papers/0213scai03.pdf}, volume = 2, year = 2013 }