A computer-implemented method for video conferencing, the method comprising: establishing a one-way or two-way videoconference between a first individual at a first client device as a service provider and a second individual at a second client device as a customer, wherein a video including a sequence of images and an audio stream is captured on a customer side; receiving (910, 1105) the video; detecting at least one object of interest in one or more of the images, the object of interest including a face of the second individual; locating feature reference points of the at least one object of interest; aligning a virtual face mesh to the at least one object of interest in one or more of the images based at least in part on the feature reference points; finding over the sequence of images at least one deformation of the virtual face mesh, wherein the at least one deformation is associated with at least one face mimic; determining that the at least one deformation refers to a facial emotion selected from a plurality of reference facial emotions; recognizing a speech emotion in the audio stream of the at least one object of interest; combining the facial emotion and the speech emotion to generate an emotional status of an individual associated with the at least one object of interest; and if the emotional status is a negative emotional status: generating and transmitting a communication over a communications network to a third party at a third client device, the communication bearing data associated with the facial emotion and data associated with the speech emotion; and entering the third party at the third client device into the videoconference between the customer at the second client device and the service provider at the first client device; wherein recognizing the speech emotion comprises: extracting at least one voice feature from the audio stream; comparing the extracted at least one voice feature to a plurality of reference voice features; and selecting the speech emotion based on the comparison of the extracted at least one voice feature to the plurality of reference voice features. establishing a one-way or two-way videoconference between a first individual at a first client device as a service provider and a second individual at a second client device as a customer, wherein a video including a sequence of images and an audio stream is captured on a customer side; receiving (910, 1105) the video; detecting at least one object of interest in one or more of the images, the object of interest including a face of the second individual; locating feature reference points of the at least one object of interest; aligning a virtual face mesh to the at least one object of interest in one or more of the images based at least in part on the feature reference points; finding over the sequence of images at least one deformation of the virtual face mesh, wherein the at least one deformation is associated with at least one face mimic; determining that the at least one deformation refers to a facial emotion selected from a plurality of reference facial emotions; recognizing a speech emotion in the audio stream of the at least one object of interest; combining the facial emotion and the speech emotion to generate an emotional status of an individual associated with the at least one object of interest; and if the emotional status is a negative emotional status: generating and transmitting a communication over a communications network to a third party at a third client device, the communication bearing data associated with the facial emotion and data associated with the speech emotion; and entering the third party at the third client device into the videoconference between the customer at the second client device and the service provider at the first client device; generating and transmitting a communication over a communications network to a third party at a third client device, the communication bearing data associated with the facial emotion and data associated with the speech emotion; and entering the third party at the third client device into the videoconference between the customer at the second client device and the service provider at the first client device; wherein recognizing the speech emotion comprises: extracting at least one voice feature from the audio stream; comparing the extracted at least one voice feature to a plurality of reference voice features; and selecting the speech emotion based on the comparison of the extracted at least one voice feature to the plurality of reference voice features. extracting at least one voice feature from the audio stream; comparing the extracted at least one voice feature to a plurality of reference voice features; and selecting the speech emotion based on the comparison of the extracted at least one voice feature to the plurality of reference voice features.